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Category: BLOG

  • Why India Needs 5G Today

    Why India Needs 5G Today

    Photo by David Becker on Unsplash

    India has over 500 million mobile telecom subscribers. The average data usage in India on mobile devices is 10 GB per month. With stiff competition and more remote work, the demand for faster data is going to increase. With 500 million more mobile subscribers to come on board in the next decade, the need for better telecom infrastructure that caters to the data needs without comprising user experience is going to be the key.

    As of today, India has approximately 400 million 4G subscribers. The major push has been due to the stiff competition created by Reliance Jio, which has enabled faster than expected adoption of 4G and created the infrastructure that is enabling remote places to access entertainment to educational content at the click of the button.

    Statistic: Number of mobile telecom subscribers in India as of December 2019, by company (in millions) | Statista
    Photo By Statista

    Compared to other countries, India has been late to the 4G party. With many countries already on 4G for more than a decade. And, advanced countries already moving to OR have already moved to 5G, which China leading with 80 million subscribers.

    Data-On-Demand is going to be the factor in enabling country foster growth from education, employment, and business point of view. 4G provides an average data speed of up to 1 Gbps, while 5G is capable of providing 20 Gbps. With such a huge difference, countries with 5G are going to leap forward in information technology by equipping academia and industry with access to Data-On-Demand.

    Any country not thinking and progressing towards 5G OR better wireless technology is going to be left behind. A country like India with 1.4 Billion population, simply cannot afford to be the one. It is time India starts implementing 5G in major metro cities which can allow the creation of infrastructure required to scale 5G country-wide.

    WHAT IS 5G

    The last four decades have shown different mobile telecommunication technologies. It started with 1G (G = Generation) which allowed wireless voice communication without any data capability. Traditionally, the mobile devices used were bulky without much power to last long.

    Then the world moved to 2G, which introduced the concept of mobile data communication along with the voice. It enabled packet-based transfer of data which could load basic HTML websites. Was perfect for business travelers as it allowed them to keep track of emails and other tools with data speed of up to 40 Kbps.

    3G which was a big jump from 2G concerning data speed. It enabled data loading of up to 30 Mbps. Now users could also watch videos apart from visiting text-based websites. It also marked the re-invention of smartphones from being keyboard to touch-based, which also came equipped with applications. It required upgrading the telecom infrastructure and was a key enabler in the digital revolution in many countries as businesses could target mobile users with numerous solutions on the go.

    Photo By Chetan Arvind Patil

    The existing 4G mobile communication technology in use in the majority of the countries was another leap in data transfer speeds. It coincided with faster, efficient, and data-driven applications that pushed the growth of smarter mobile devices. It also provided the real meaning to HotSpots that allowed people to access high-speed data on the go. 4G also ensured the growth of the digital video services for entertainment and education by providing networks of high-speed infrastructure that allowed data transfer up to 1 Gbps.

    5G is a big leap forward. It is not just about mobile device communication, it is more about making all the infrastructures smarted. It is capable of ensuring high data communication is available on demand for any smart device. From buildings to trains, to airplanes to cars and businesses are going to be needing on the go data access and 5G is capable of providing it with up to 20 Gbps data speed. It is also expected that 5G is going to drive XR reality to its true potential.

    Post COVID-19 is going to ensure that every business is digitally equipped and in a country like India which such a vast diverse population needing different services and contents, 5G is going to be the enabler of 360-degree growth.

    5G IN INDIA

    Without a proper telecommunication infrastructure, 5G growth and adoption is not possible. There are many aspects that need to be upgraded to implement 5G. For India, the following two will be the key factors:

    5G SMART-INFRASTRUCTURE

    Without upgrading the current 4G telecommunication infrastructure to 5G it will be impossible to drive adoption. The existing 4G user base will have to kept catered without any issues and hurdles while upgrading the telecommunication wireless networks to make all the communication capable

    This will require big investments, and with the way things are going in India’s telecom sector, capital expenditure is going to be the last question in everyone’s mind. 5G will not be only about mobile communication but also in a soon everything connected world, the demand for 5G will be 10 fold and that will mean taking a smart look at the infrastructure

    Photo By Chetan Arvind Patil

    5G SMART-DEVICES

    Not only 5G networks will have to be upgraded, but the end-users devices also have to be equipped with 5G electronic chips. The solution of 5G is already present in the market. Many smart device manufacturers have already introduced 5G capable devices

    For India, the key will be to lower the cost in order to ensure that more than 500 million users with existing 4G enabled devices are tempted to move to 5G capable devices5G might also lead the invention of new spending model for smart devices that will be more towards data to cost rather than device cost.

    5G OPPORTUNITIES IN INDIA

    The adoption of a faster network like 5G is only going to push the digital innovation to the next level. With numerous online training, certification, and education content apart from entertainment options, the opportunity that 5G will present is enormous.

    5G is going to create employment for people with skills to develop and manage smart infrastructure around it in India. It will act as a catalyst in inviting foreign companies to set up research and development centers along with manufacturing units to create large numbers of smart devices that will be required.

    The auto industry that is well set in India will see another round of innovation with cars equipped with 5G features to make them safer and smart. It will drive faster consumption of content and information which will also mean faster creation of content and data required to meet the demand.

    Photo By Chetan Arvind Patil

    Cross reality is touted to be the next-big-thing in the information exchange sector. With 5G’s faster and reliable connectivity, virtual reality, mixed reality and cinematic reality is going to see growth and innovation which has never been seen before.

    5G HURDLES IN INDIA

    One of the key requirement for 5G in India is the allocation of spectrum. Without the official allocation of spectrum, it will be difficult to create infrastructure. 5G spectrum cost is also going to add pressure on telecom companies and they might not be keen to implement and upgrade the infrastructure. Eventually, any high spectrum cost will be passed on to the subscribers. One more hurdler is choosing the preferred technology partners.

    Currently, Huawei being one of the leaders in 5G infrastructure creation and being a China company is going to add another hurdle with the Government of India not keen on critical in structure involving companies from China. India’s Jio is hoping to make in house 5G infrastructure to tackle such a situation. It will be interesting to see how it works out, but in the end, the solution also needs to come from other telecom service providers to ensure a fair market.

    2020 was supposed to be the year when 5G spectrum allocation was to take place, however, it has been postponed to 2021. With another year gone, and China already having 80 million 5G subscribers, India is going to be behind in 5G innovation.

    With COVID-19 showing the way of changing the working environment, India will be left far behind if 5G spectrum allocation does not take place at the earliest.

    For India’s digital growth it is vital that 5G implementation starts today and not tomorrow.

    5G WILL ENABLE DATA DEMAND AND DATA SUPPLY COMPETITION

    PSA

    Qualcomm is one of the leaders in 5G wireless solutions and the talk by John E. Smee on 5G evolution is really interesting.

  • The Future Of Information Exchange Is Contactless

    The Future Of Information Exchange Is Contactless

    Photo by Phix Nguyen on Unsplash

    The most critical piece of the global village is the information exchange. In the last few decades, it has moved from wired telephones to wireless and then today runs on top of an interconnected network of computers called the internet.

    The exchange of information during pre-COVID-19 was a combination of contact and contactless. In contact information exchange one-to-one communication was the key to working and developing things for good. However, post-COVID-19 the new normal will be contactless, which is getting adopted much faster than expected.

    Picture By Chetan Arvind Patil

    Contactless Information Exchange (CIE) will find its way into many aspects of life rather than just technology-enabled solutions. CIE is going to make humans far more technology-dependent than they are now. Whether it is driving the car, paying for bills, restaurant outings, etc., every day to day activity is going to see CIE incorporated by default.

    PAYMENT

    Contactless payments are the first major shift that post-COVID-19 is going to bring. Even today in North American alone 50% of the transaction are non-cash mode.

    More and more people are using contactless payment with around 51% of the U.S. payment transactions were contactless mode in the last 6 months. The trend is only going to go up. In Europe, the contactless payment has seen a 97% increase in the last two years, and over the next one year, it is being predicted that almost 100% of the credit and debit card transactions in Europe are going to be contactless.

    There are major benefits of contactless that includes paying without touching different devices. A traditional process of using credit or debit cards at the store often requires handing over the card to the shop owner and then he/she using it on the point of sale (PoS) system. All this process is not pandemic friendly and going on in the future, PoS will be history.

    Change in mode of payment will also dramatically change the equipment business that serves the payment industry. PoS will make the way of wireless technologies like MIFARE, which can securely allow the exchange of information for a service.

    Even smartphones using Square Reader will start coming up with inbuilt systems that will allow contactless payment options. This is going to drastically reduce the cost of accepting payment for small merchants who often end up paying not only for the PoS portable device but also the percentage of the payment received.

    Questions are being raised about security around contactless payments, however, it has been proved again and again that contactless payments are much more secure than traditional contact-based transactions.

    SHOPPING

    Amazon has already shown the world how the future of shopping is going to be contactless by introducing Amazon Go experience. Even though the majority of the shopping during COVID-19 has moved to eCommerce, the traditional way of shopping is going to stay. People would always be willing to go out spend quality time with family and still will be willing to experience the joy of buying in-store.

    What is certainly going to change is that more and more big stores like Walmart etc., are going to ramp up their back end that will not only cater to those shopping in the store but to also ordering online. All of this will be geared towards being contactless.

    IKEA already has shown how one can take advantage of the big store experience by not only catering to the in-store experience that includes dining but also ensuring how the warehouse can be connected to the back end allowing the online experience to be as good in the store.

    Many of the stores are already providing home delivery of goods, but that experience will still take time to scale at large. Part of the reason is being comfortable with someone else coming in contact with your groceries in the post-COVID-19 world. Even though the majority of the delivery services are COVID-19 complaint. With Postmates getting acquired by Uber, the future for door-to-door delivery looks promising.

    In India, Reliance Industries homegrown JioMart has already started connecting the small shops with consumers. This is going to shake up the whole industry with families preferring doorstep deliveries that option to go out.

    Post-COVID-19 future of shopping is not only going to be contactless but the whole experience is going to change.

    TRANSPORTATION

    Moving of goods from one point to another has traditionally involved using trucks for smaller distances. Within cities and towns, much smaller systems are being deployed. Post COVID-19 is going to see the increasing deployment of driverless delivery carts that will reduce the number of contacts for a shipped well drastically.

    In 2017, self-driving trucks were deployed for testing. In 2020, they are ready to take the industry. The approach self-driving trucks are going to bring is ensuring that the goods are picked from the source location and delivered to the destination without stops and that is going to ensure that the goods are safe and went through the contactless process.

    Consumer Brands has already formed a task force to ensure that the future moves to contactless delivery as soon as possible.

    DINING

    Outings are part of life, no one feels being at work and home all the time. The restaurant industry took the biggest hit during COVID-19 with the majority of jobs being lost in this sector. COVID-19 has increasingly prompted the need to ensure that the dining experience also changes in the future.

    Food is a product that does require lots of contacts and it is not possible to make dinning a 100% contactless experience. To ensure that the orders are placed and ready for dining, the future is going to be a move towards pre-orders where the food is ordered before the consumer leaves the house and by the time he/she reaches the food is ready to eat.

    Another approach that is going to involved contactless dining will be placing orders at the restaurants using an application rather than letting servers take the orders.

    There are already many solutions out in the market for restaurant business but the major impact is going to be the additional cost that restaurant owners will eventually have to pass to consumers to survive in a competitive industry.

    HEALTHCARE

    COVID-19 was all about health and well being. There is going to be an increasing need to monitor the health and ensure that the individuals are free of diseases that might turn into a pandemic.

    The Healthcare industry requires the diagnosis of patients and doing it without being in contact is difficult. What the healthcare industry can do is to eliminate the pre and post patient examination process more contactless.

    It is going to involve screening using tools that can detect and advise physicians of steps in advance. Remote sensing is going to be another solution that will be deployed at a larges scale not only in hospitals but in places with more crowd.

    Remote monitoring of patients post-diagnosis is going to be the default way of working in the health care industry. It will eliminate the number of contacts that patients have with others.

    Telehealth is going to be the first point of consultations for non-life-threatening diseases. It is going to also enable many technological solutions like Cross Reality

    Contactless Information Exchange is going to be the future of communication and is going to be the new normal. It will be interesting to see how new solutions are built around the existing technology to provide contactless services.

    Contactless might open up whole new industry and possibilities.

    PSA

    McKinsey&Company has a very informative take on how operations around contactless will evolve in future.

  • The Challenges For Electric Vehicles In India

    The Challenges For Electric Vehicles In India

    Photo by CHUTTERSNAP on Unsplash

    ELECTRIC VEHICLES IN INDIA

    India has set an ambitious goal of 30% electric vehicle (EV) adoption by 2030. The adoption is expected to be driven majorly by two/three-wheelers and commercial vehicles. This is a daunting task and there are many challenges on way to ensuring faster EV adoption.

    EV adoption requires a three-way handshake and the same is true for the Indian automotive market:

    • First: Automotive manufacturers need to provide an EV alternate to every non-EV model in production
    • Second: Consumers should be able to afford the EV model
    • Third: Infrastructure required to ensure end-to-end EV support

    The majority of automotive manufacturers around the world have already started working on plans to launch a wide range of EV vehicles for consumers. Some are also working on an alternate EV model for every alternate fuel model in production. The more manufacturers join such initiative, the better it will be for a new market like India.

    From the consumer point of view, the major concern is still about the range and the cost. Over the last 5 years, several startups in India have focused on EV solutions to capture the two/three-wheeler market. Some have been very successful in doing so. There are still concerns around the cost and range, as these two/three wheelers still take on an average of 5 hours to get fully charged to provide a range of about 150-200 KM (93-125 Miles).

    Infrastructure is another key to the wider adoption of EV. Countries that have a well-developed market for EV (the USA, EU, etc.) have ensured that the policies are suitable for faster EV adoption including incentives for both manufacturers and consumers.

    India though has taken a step in all the three points discussed above, there are still challenges on the EV 2030 roadmap.

    EV CHALLENGES IN INDIA

    EV growth in India is depended on overcoming the following challenges:

    • Cost
    • Range
    • Option
    • Environment
    • Infrastructure

    Cost: Given the technology required to develop an efficient EV is fairly new, the cost is becoming the major hurdle in wider adoption. The majority of India’s automotive buyers focus on vehicles that are compact and provide long-term reliability and cost benefits. This choice has driven automotive manufacturers in India to keep churning out new models that are not only compact and reliable, but are low cost too. Any new EV passenger vehicle will have to not only beat the entry-level fuel-powered models but will also need to ensure that there is no compromise on the features.

    Range: India is still a fuel-powered automotive market. Users have adapted to the fact that they need not worry about waiting to re-fuel the vehicle. Not all the cities and towns have the EV electric charging infrastructure. On the go charging requires time and that doesn’t help EV adoption. This is a turn off for the EV market. On top, the planning and implementation of such EV charging network is yet to be defined clearly for the Indian market.

    Picture By Chetan Arvind Patil

    Option: In 2020, Indian automotive manufacturers are not providing more than two or three EV model options. This limits the EV options for the consumer. While commercial vehicles by default are slowly getting more EV models, the major market (~70%) is still in the passenger vehicles which is far behind in terms of EV models. Unless automotive manufactures come up with a wide range of options, consumers will still get attracted to fuel-powered vehicles.

    Environment: There is still no clear roadmap in India about how the battery charging infrastructure is going to be. Whether it will be re-charging the EV batteries at the charging stations or the battery swapping is going to be an economically viable option. In both cases, the environmental challenges still exist. Taking fossil fuel out of the vehicles still does not mean that the EV is 100% environment friendly. Disposing of the battery after long usage is still a big concern. On top, the raw materials required to develop batteries are not fully environment friendly.

    Infrastructure: EV requires a network of charging stations. The developed market already have policies and partners who have worked on creating a network of infrastructure that allows anyone with an EV model to get their EV charged at an affordable cost. The same infrastructure is now being extended to provide EV servicing, in case of breakdowns. India needs a clear policy and partners to ensure that the infrastructure is in place before ramping up the EV production.

    EV FUTURE IN INDIA

    The future of EV is promising in India. It does come up with challenges. There are already established EV markets to learn from and take the best possible route possible to increase the wider adoption of passenger and commercial EV.

    The commercial EV market is growing mainly due to state government policies. The same needs to be applied to passenger vehicles. Two/three-wheelers have already started adopting to the EV business model. If the cost goes down further with an increase in range, the speed of adoption can be faster.

    EV market also provides opportunity to the semiconductor companies which can provide electronic based solution to make EV ecosystem smarter.

    The mass mobility transition for 1.3+ Billion people is not an easy task. It is an opportunity for all the manufactures that are driving the EV market around the globe. Will be exciting to see how the world helps India drive into the EV world.

  • The Future of Education And Learning

    The Future of Education And Learning

    Photo by Changbok Ko on Unsplash

    Education is the key to learning various aspects of life and different career options. It enables the development of skills. There have been different way to learn in order to enable individuals with wider thoughts and options from career point of view.

    Many prefer the traditional way of education by enrolling in schools/universities to acquire certificate/degree/diploma after fulfilling required criteria. On other hand few also prefer to learn everything on their own from different sources whether it is library, internet or attending different events, workshops and conferences. This may not lead to a formal certificate/degree/diploma, but the goal for such learners is not credentials.

    Whichever path one takes, it always leads to same goal: Education and Learning.

    In the last decade, there has been lot of changes in the form of delivery of education and different modes of learning. Majority of the changes have been due to the advancement of technology that has allowed the content to be delivered easily, mainly thanks to the innovation due to internet and connectivity.

    With such abundance of sources readily available at the click of the button, the mode of learning is going to change from Traditional Education to Always Be Educating And Learning From Anywhere.

    Lets take a look at different forms of sharing knowledge and educating people, and also how it has evolved by building on top of previous mode of education delivery.

    PRE-INTERNET TRADITIONAL LEARNING

    What And How:

    • This is the 101 form of education where schools and universities were established. Students will enroll and follow a set curriculum before earning the certificate/degree/diploma. This still exists, but slowly it is adapting and finding ways to make it more convenient rather than moving to a location to acquire knowledge.
    • One of the key benefits of traditional learning is the massive one-to-one interaction students have on daily basis. This not only allows growth from education and knowledge point of view, but also help students develop. networking and interpersonal skills. On top, individuals can engage in extra curriculum activities that can help them physically, socially and mentally.
    • Another key driver of traditional learning is research and development (R&D). R&D is key to future developments. Even internet which you are using today to read this blog was a R&D project. And, today it is the backbone of everything in the world.
    • There has been growing concerns and questions on the need to have traditional learning, however it is key to many future advancement along with innovation leading to better quality of life.
    Photo By Chetan Arvind Patil

    Problem Solved:

    • Interaction with peers
    • Learning future options
    • Extra curriculum development
    • Access to the formal education

    Problem Created:

    • Become more routine task
    • Difficult to find the best teachers
    • Started getting expensive to afford
    • Not all schools/universities have the same facilities, resources, financials and quality

    PRE-INTERNET TRADITIONAL LEARNING VIA DISTANCE LEARNING

    What And How:

    • One of the major drawbacks with traditional learning is that one has to be physically present in the place where the schools/universities are located. This started becoming a problem for those whose town/cities were lacking educational institutes.
    • Another gap that traditional learning created was that the quality of education started varying from place to place. Few will have the best of facilities and teachers, and rest will always try to balance thus leading to imbalance. This started depriving students the opportunity to learn from the best if they cannot afford to enroll/move.
    • Eventually, all these problems lead to the invention of distance learning. Which allowed students to enroll in the best schools and universities without having to be physically present.
    • The content and material related to the classes is provided as per the schedule via snail mail. Then at the end of the season students can take exams at local centers. The outcome the decides whether they get to hold the certificate/degree/diploma from the coveted schools and universities.
    • Distance access to best schools and universities lead to increase in literacy and opened employment opportunity
    Photo By Chetan Arvind Patil

    Problem Solved:

    • Adaptive scheduling and enrollment
    • Low cost compared to traditional learning
    • Made individuals eligible for higher education
    • Access to formal education from the best schools and teachers over correspondence

    Problem Created:

    • Lack of in person interaction with teachers and peers
    • With growing option it became difficult to choose the best
    • Even industry started to question whether distance learning is legit
    • Practical learning was not part of correspondence due to lack of physical access to the labs

    POST-INTERNET HYBRID TRADITIONAL LEARNING

    What And How:

    • Post internet many things changed and allowed learning being more a mix of traditional and online, also knows has hybrid traditional learning.
    • Distance correspondence courses were now offered online in real time. Schools and teachers were now equipped with more knowledge and advanced technological tools.
    • Most of the students who can afford will enroll in person and those who cannot started opting for online mode of learning. Both ways allowing access to same education.
    • Curriculum of the courses that required labs were adapted for online students.
    • Course material distribution started happening via online websites and software rather than physical distribution of assignments as hard copy.
    Photo By Chetan Arvind Patil

    Problem Solved:

    • Access to the courses in real time
    • Option to enroll in online mode of learning
    • Materials can be accessed anytime anywhere
    • Made education more exciting and little bit affordable based option to enroll courses online rather than in person

    Problem Created:

    • Education became fast paced rather than learning based
    • Not all courses were taught online, thus the options were limited
    • Not all major were able to make most of it like medical education where one needs to be with patients as the course moves forward
    • Everyone’s learning was depended on the mode of education opted. Those with in person option had better access to teachers than those using online mode

    POST-INTERNET HYBRID TRADITIONAL LEARNING WITH OVER THE TOP CONTENT

    What And How

    • Over The Top (OTT) is a way of providing services on top of existing services. For example, a cellular company providing educational apps on top of the voice service it provides. A startup with extra curriculum to create existing course more interactive is another example of OTT.
    • OTT in education applies to both teachers and students. As it is designed to make both the traditional and hybrid approach better
    • There are third party companies that tie up with schools and universities to ensure that learning is more interactive, practical and is built on top of years of research carried out across the world.
    • OTT is not just about learning to seek certificate/degree/diploma, it has different modes too:
    Photo By Chetan Arvind Patil

    Problem Solved

    • Made education more fun
    • Improved quality of courses
    • Increased real time interaction of students and teachers
    • Practicals become more knowledgeable based based on real life examples

    Problem Created

    • Not all schools and students could afford the OTT services
    • Additional cost and time to learn courses other than traditional curriculum
    • Not available to villages and towns which are still lacking resources and finance
    • It made education more expensive as the OTT fee was passed on to the students

    FUTURE OF EDUCATION AND LEARNING

    COVID-19 drove closure of schools and universities around the globe. This forced cancellation of academic session in many countries. Places where schools/universities that had the infrastructure were able to switch to online mode and complete the curriculum. This also drove demand of online mode of learning. Also pushed workshop and conferences to make use of webinars to deliver the per-scheduled content.

    In future, learning instead of being just about attending classes will move to always be educating and learning from anywhere. It will not matter where the content is coming from, education seeker will keep learning from different resources as per their need and requirement. They will also continue to seek traditional credentialing process to widen their reach and networking.

    Photo By Chetan Arvind Patil
    Photo By Chetan Arvind Patil

    Future of education and learning is everywhere:

    • Traditional learning will be the foundation
    • Mixed reality will enable virtual laboratories
    • Peer mentoring will be vital part of curriculum
    • Hybrid approach with option to attend classes online and/or offline
    • Distance learning in form of special issues and books for remotest areas

    Whether or not formal credentialing in form of certificate/degree/diploma will still exists is left for expert to talk about. However, adapting and learning from different sources is going to be very vital and key skill of next generation. This will also mean countries across the globe will have to have reliable and affordable digital infrastructure.

    Always Be Educating And Learning From Anywhere

    PSA

    Steve Blank‘s talk on The Secret History of Silicon Valley shows the importance of how traditional education driven by research and development enabled the foundation of Silicon Valley.

  • The Data-Driven Approach Towards Semiconductor Manufacturing

    The Data-Driven Approach Towards Semiconductor Manufacturing

    Photo by Vishnu Mohanan on Unsplash

    THE GROWTH OF DATA IN THE SEMICONDUCTOR MANUFACTURING

    The growth of digitization has led to the generation of massive amounts of data on day to day basis. The data explosion has pushed several industries to adapt to data-driven analysis and decision-making processes. The same is true for the semiconductor industry.

    Data was always an integral part of semiconductor design and manufacturing. The need for data has increased further due to the cost and risk involved in designing products that are becoming smaller and smarter. The cost to fabricate semiconductor products is high and that is why during the design phases innovative simulations/modeling approaches are used to validate product design against specification before sending the final design files to the semiconductor fabrication houses. The risk of not spending time to collect and review semiconductor data both during the design and the manufacturing stage can cost a lot of money and time if the product starts failing in the field. 

    Data-Driven Approach Is Raising The Bar Of Semiconductor Manufacturing

    As the technology-node and package technology have advanced, so needs to take a data-driven approach to semiconductor manufacturing. The goal of the data-driven approach is to ensure that the products being are defect-free. The sophisticated tools and equipment used by the semiconductor manufacturing process have only gotten more advanced. The de-facto feature of these system-driven tools is to capture data and present it in a form that makes the decision-making process easier and faster.

    The data-driven approach is required to meet the following two important requirements of semiconductor manufacturing:

    Quality: Qualifying every semiconductor products is vital. It has to meet different industrial standards. Automotive semiconductor products have to go through one of the most stringent qualifying processes to ensure the product can work seamlessly everywhere. It is vital to ensure the manufacturing process established meets the high standards of quality requirement, which is possible only if the data captured to drive the decision-making process.

    Waste: Every data point tells a story. In semiconductor manufacturing, data can be about the design or the manufacturing tools, or handling issues, and many more. Every semiconductor data type counts towards ensuring the wafers and assembled parts are not getting scrapped. Scrapping raises yield concerns and indirectly impacts the cost.

    Without investing time and money in the data-driven approach to manufacturing semiconductor products, the semiconductor companies run into the risk of overlooking the quality metric. Driven by the need to ensure the products using the semiconductor solutions meet user satisfaction, the customers/companies using the semiconductor products are increasingly using Defective Parts Per Billion (DPPB) as a new metric than Defective Parts Per Million (DPPM).

    The need to capture, process and review semiconductor manufacturing data is becoming vital when there is a possibility that the semiconductor device might end up powering critical infrastructures likes satellites to aerospace to automotive (and many other solutions).

    All this is why the semiconductor industry is becoming more data-driven than ever before. The manufacturing part of the semiconductor process is not complete without letting the data speak.

    Picture By Chetan Arvind Patil

    THE PROCESS TO CAPTURE DATA IN THE SEMICONDUCTOR MANUFACTURING

    The semiconductor manufacturing process is a well-established flow. While every product has different requirements driven by the specification it is supposed to work within, some standard flows/stages are common across numerous semiconductor products.

    These processes use tools/solutions/recipes to capture data, which eventually drives a data-driven decision-making approach in semiconductor manufacturing.

    Following are the major process that leads to capturing of semiconductor manufacturing data:

    Fabrication: The first step towards semiconductor manufacturing is to fabricate the product on the wafer. Every layer/mask/stage of the semiconductor device fabrication is data-driven. If the data does not align at the etch or the lithography stage (for example), the wafer/lot cannot move forward. Several modules are placed in the kerf region of the wafer to data of the devices (that eventually make up the full die) to ensure is no deviation in the semiconductor wafer. All this data is unique to the technology-node. At the end of the wafer fabrication, data in the form of visual images ensure no particles or scratches are present on the wafer/die.

    Wafer Test: The defect-free wafer coming from the semiconductor fabrication facility gets sent to the test facility. The wafer test stage ensures all the die on the wafer gets electrically tested with the test program to validate whether the die meets the specification or not. The good and the bad die are marked accordingly. All this is possible due to ATE tools and probing hardware. The data is analyzed to understand any excursion, which eventually gets debugged to ensure no test escapes. 

    Final Test: The final test can be performed on the wafer (Wafer-Level Chip Scale Package (WLCSP)) or on the assembled parts (non-WLCSP). The final test uses similar testing criteria and tools like the wafer test). The major difference is the packaging testing versus dies testing. The data points are specific to the package testing. This is often the last electrical data point the semiconductor manufacturing process generates before the parts are shipped to the end customer or assembly.

    Assembly Inspection: Post assembly, the visual inspection of the assembled parts is carried out. The tools used for visual inspection capture all sides of the assembled parts. The data in the form of images show if chipping/defects occurred during the assembly process. If so, then the root cause needs to be determined. The data in the form of images often requires a highly automated system to alert any defects.

    System Testing: A final system (like a smartphone) not only uses one specific semiconductor product but several others. All the different semiconductor products are assembled onto the Printed Circuit Board (PCB) and should work in harmony. If anything fails, then the data relevant to the failing semiconductor product is capture and sent to the company that fabricated it. System testing also drives the semiconductor manufacturing process from the customer side.

    Miscellaneous: The last data point in the semiconductor manufacturing are from the equipment that enables the different process. These need periodic maintenance to avoid breakdown. All the equipment connected via a Manufacturing Execution System (MES) is monitored to capture every activity the equipment/tools perform. This data is vital for keeping the semiconductor manufacturing facility up 24x7x365.

    The above data points are vital in ensuring the semiconductor manufacturing process is fabricating/testing the high-quality products that meet the stringent quality requirements. To ensure, the high-quality demand data-driven process is critical in semiconductor manufacturing.

    Picture By Chetan Arvind Patil

    THE ADVANCED DATA APPROACH IN THE SEMICONDUCTOR MANUFACTURING

    Even though data exploration in semiconductor manufacturing is not new, the need to take a different data analysis approach is growing. The main reason is due to the high cost required to generate the semiconductor data. In the smallest data available, the semiconductor engineers need to predict that the products will work in the market as per the specification.

    To lower the time taken to move the wafers to the next stage, the semiconductor manufacturing process is relying on different advanced approaches to enable data-driven semiconductor manufacturing:

    Algorithm: Due to the proliferation of fast systems that can crunch data on the go has led to the development of algorithmic solutions that can detect scratches, clusters, excursions, particles, etc., faster than ever. The algorithms deployed can capture the patterns to raise an alert if there are issues with the semiconductor manufacturing process. These algorithms take the help of numerical data or visual data. Visual data is more vital as it shows gate-level details using an advanced microscope. There are already solutions, but there is a need to minimize the time taken for decision making as spending more time to decide on the correctness of the product means holding the lot/wafer from releasing, which can be costly.

    Analytic: Data lying without insights is not useful. Given that every die/chip that gets shipped out of the semiconductor manufacturing flow is visualize/tested, it is important to develop an analytical approach that uses computational analysis of statistics to drive data exploration. It helps the semiconductor data engineers to visualize data using diverse statistical methods to find issues/outliers. Analytical solutions are already available in the market/industry, but often requires skills to look beyond what is being presented on the dashboard.

    Tool: Tools are required to view the detailed history of every die that gets manufactured. The standard process to capture and store is already defined. The end-to-end semiconductor manufacturing data analysis still requires different tools to visualize and critically analyze the data. One single data tool may not be enough. It is good to test and use data analytical tools (or programming methodologies) as per the need to drive the decision-making process.

    Decision: Eventually, the goal of data analysis in semiconductor manufacturing is to either hold or release the product. It requires the perfect combination of computer and human. Computers can enable data collection and storage. However, the data wrangling is still on humans. In semiconductor manufacturing, every new data requires a new inspection approach as every new product is different from the last one. All this means every changing data-driven approach to decision-making (hold or release).

    The speed at which the semiconductor industry is driving towards the shirking technology-node year-on-year, the process to scrutinize the data will also change, and the semiconductor data inspection process will keep getting directed towards new ways to enable the smarter data-driven approach towards the semiconductor manufacturing.

  • DataCare Is HealthCare

    DataCare Is HealthCare

    Photo by National Cancer Institute on Unsplash

    HealthCare has always been data-driven. Doctors always evaluate patients based on pointers like temperature, heart rate, and past health history that might have contributed to patient’s health.

    There are many critical data points that the human body generates every second. Each of these data points if captured correctly can allow physicians to diagnose better, and can also alert the patient and the hospitals about deteriorating health conditions by predicting based on data points from the human body.

    Health Data Points Human Body Generates

    The human body itself can alone provide many data points that can aid diagnosis at the source. At the top level, there are ten key major points: Skin, Urine, Saliva, Sweat, Blood, Breath, Balance, Heartbeat, Movement, Brainwaves, and Temperature.

    Photo By Chetan Arvind Patil

    Each of these data points when captured correctly using industry-standard biosensors. Some of these data points require bulky setup around the body. However, with new inventions in bio-technology the size of each of these instruments is decreasing. The major reasons are the advancement in the sensors that are used to capture each of these health data points.

    It is important to correctly and accurately capture these points. There are already FDA approved biosensors and portable devices that can not only capture these data point, but also post-process at the source. After post-processing the data along with preliminary diagnosis can be presented to patients along with authorized doctors and hospitals.

    There are already solutions in the market to capture and analyze each of these human health data points at the source:

    Tissue Analytics has an innovative solution to capture the image of skin wounds and then sending it for diagnosis helps patients in understanding the severity of the skin related issue

    Healthy provides clinically-validated digital urine analysis. With the help of strips and smartphone, one can perform primarily urine analysis at home

    23andMe provides saliva-based DNA genetic testing and analysis unlocks a lot of data points related to health and ancestry

    Glooko has developed a mobile app that allows blood data logging at source and is also compatible with many diabetics devices. The data captured then can be shared with an authorized care team to provide better diagnosis

    Keyto provides breath sensor devices that can help people keep track of the ketogenic diet

    Zanthion developed balance sensor-based balance and detection solution, which can automatically alert authorities in case of severe falls

    Cardiac Insight manufacturers portable devices that can collect heartbeat information to monitor cardiac activity real-time

    Fjuul makes use of mobile sensors to provide movement-related data points. Such data is vital to understand fitness and gauge health issues. This data point then can also be used by insurance providers to adjust premiums

    BrainCo has a kit that can be worn around the head to capture brainwaves to provide EEG data points

    Kinsa developed portable devices to keep track of body temperature, which can then be logged into a mobile app

    Future Health Data Points Will Have To Be Connected

    There is no question that healthcare has embraced technology and with more data, and computer-intensive systems, it is only going to get beneficial for healthcare research.

    However, the buck doesn’t stop here: It is not viable to expect patients to have ten different devices and apps to ensure full body continuous monitoring. Without a connected smart integrated health monitoring system, it is not possible to capture all the human body data points. Every health activity in the body is providing vital sings for future health issues.

    Photo By Chetan Arvind Patil

    Post COVID-19, the next big thing for healthcare is to enable continuous monitoring to take pro-active measures.

    To achieve true continuous monitoring, it is critical to first connect all the possible health data points that patient’s body generates. Then, the second task is to interface individual data from all possible patient population. These two infrastructure when combined together will enable prediction of not only outbreaks like COVID-19, but will also provide information about how patients from specific age groups differ in terms of health activities.

    Such data when used for good, can unleash endless opportunities.

    In short, connected continuous monitoring means:

    • Single smart health wearable device that can capture all the ten major data points for all the population possible
    • Connecting patients data with research data, genetics, pharmacy, health insurance providers, labs, and medical Record for continuous monitoring
    • Storing, analyzing and presenting results to ensure pro-active actions
    • All done securely on privacy backed infrastructure

    Continuously Connected Smart And Securely Driven Technology Infrastructure For DataCare Is The Future Of HealthCare

    PSA

    Prof. John A. Rogers and his group at Northwestern University has been at the fore-front of wearable technology for health care. They have also developed solutions around COVID-19 to continuously monitor and predict symptoms.

  • Data Enabled End-To-End Manufacturing

    Data Enabled End-To-End Manufacturing

    Photo by Laurel and Michael Evans on Unsplash

    Industry 1.0 was all about the transfer of manufacturing from humans to machines. Industry 2.0 increased productivity by using technology-enabled information and faster transfer of goods. With Industry 3.0, computers took over machines and allowed efficient manufacturing compared to Industry 2.0.

    Today, we are in Industry 4.0. This is all about data gathering at each stage of end-to-end manufacturing to allow the right product at the right place at the right time with minimal waste and downtime.

    In order to fully achieve Industry 4.0, there is a need to understand how efficiency can be achieved, and to do so one has to look at each stage from a data point of view. Without capturing data information at every stage of manufacturing, it is difficult to remove bottlenecks.

    Photo By Chetan Arvind Patil

    PROCUREMENT

    Procurement is the defacto process for any manufacturing domain. Does not matter what type of products are being developed, manufacturers have to keep track of inventory.

    During the pre-computer era, this process required manual bookkeeping and then actions would need to be taken based on when raw materials are going to be out of stock. This meant the raw materials were ordered without understanding whether the market demand, thus leading to waste of manufactured goods and money.

    In the post-computer era, this process moved from books to computers. Software was deployed that could keep track and alert beforehand. However, this process was still similar to the pre-computer era, except that humans could do be used for more productive work than bookkeeping.

    Photo By Chetan Arvind Patil

    In today’s day and age, the need is to make procurement more real-time, smart and market demand-driven. Toyota Production System follows the concept of Just-In-Time (JIT) manufacturing since the 1970s. It is more relevant today where cost saving is critical while ensuring market demand is met. In order to achieve efficient manufacturing, data from different vendors need to be connected in real-time. This allows the end customer to understand how late OR how early they should procure the raw material based on the demand of the product.

    Enterprise Resource Planning tools are increasingly being used to provide such solutions. However, they cost a fortune to deploy and manage. Dedicated teams are required. A big enterprise might find it easy to make use of such tools, but small manufacturers will financially struggle to get such a system deployed.

    With the advancement in connectivity and computing if such gaps can be filled while ensuring minimum impact on the expense, then procurement (the stepping stone of manufacturing) can be made more efficient by tapping into the data information.

    MANUFACTURING

    After procurement, comes the real task of manufacturing. When goods are being manufactured the focus is on cost efficiency by achieving maximum uptime with minimum downtime. We are living in an always-on world, where things need to keep running 24×7 to achieve more profits year on year. The same applies to machines that are churning out goods. Here too, does not matter what domain is being catered; machines and tools need to be up and running all the time. An idle machine in manufacturing is a liability.

    In order to achieve 100% uptime, a critical factor is to predict downtime. Predictive downtime requires capturing real-time data. Data can be about how old the parts are, have parts are aging based on usage, when should parts be replaced and serviced, when should machine go through calibration, is demand going to keep machine idle, how can resources be planned efficiently and many other data points.

    Photo By Chetan Arvind Patil

    Oil and gas production has to be up and running 100% of the time. To achieve 100% uptime, the oil and gas industry has taken an advanced approach and adapted to data-enabled production. Manufacturing in today’s date is not just about production engineering, it has to have a data engineering aspect where data is captured, stored, analyzed, and presented for pro-active action.

    Capturing all such data points and presenting in a single dashboard can provide much more insight into the manufacture than waiting for the machine to go down. All of this requires a drastic change in the way of working so that resource planning for manufacturing is made more data-driven. Data-enabled manufacturing solutions are already present and it is time many manufacturers start taking data aspect into production to achieve 100% uptime.

    TESTING

    Testing is the most critical process during manufacturing. Now only the product should meet all the requirements under quality, reliability, and operating conditions, the data generated during the testing process should also be analyzed thoroughly and stored in case of any customer return.

    Photo By Chetan Arvind Patil

    The last thing the manufacture wants is another Samsung Galaxy Note 7 situation where the smartphone exploded due to faults in the battery. Depending on the product the test data can be captured using different tools and processes. This requires implementing a software interface that can log the data during the testing process. Then, based on the specifications applicable, it can be then put through different operating conditions, quality, and reliability checks before putting through interface testing for a real-world application.

    Today, there are different analytical tools that are available in the market that are proving to be critical for productivity and probability. Data generation, data analysis, data action, and data storage in itself going to be a trillion-dollar industry. The solutions provided for manufacturing analytics with respect to testing are many. It is critical for product development and manufacturing companies to embrace and find ways to implement data-driven testing within the manufacturing cycle.

    After all the testing and quality requirements have been met the product can move to the next stage of manufacturing.

    PACKAGING

    In the US alone, 165 Billion packages are shipped every year and this is just e-commerce data. 50% of these packages end up being waste and not getting recycled. This clearly points to the need to make packaging more efficient.

    LimeLoop and Repack provide solutions to enable re-use of packaging. However, this requires tracking of where the package is being used and then need to re-ship the empty packages. This is not a practical solution for a custom manufacturer dealing directly with businesses that are not into e-commerce like car manufacturers, electronic design and manufacturing, and many other domains.

    In order to achieve efficiency in packaging, manufacturers need to follow data enabled packaging by considering following points:

    • Quality
    • Waste
    • Usage
    Photo By Chetan Arvind Patil

    Quality enables whether the product being manufactured and being shipped in certain packaging meets the required industry standards. This means tracking the data points of happenings with respect to packaging. The old-age process of using cardboards to package is only going to add cost and eventually leads to waste. To understand where cost savings can be achieved, it is critical to capture data points on the usage of the package. All this eventually allows innovation within the packaging domain to make more informed decisions.

    For example: Is there a way to package products in small form factors which can in turn save packaging cost including on shipping? This cannot be achieved by package innovation, which requires data capturing of the packaging within the manufacturing unit.

    LOGISTICS

    Out of all the blocks of manufacturing, logistics is the most advanced and has embraced data faster than any other sector. It has been the leader in data usage and driving it for the efficient delivery of goods.

    For manufacturer data usage in logistics means tracking the market for the least expensive way to ship the goods from point A to point B. Traditionally, big manufacturers try to save cost by means of entering contracts with giants like UPS, FedEx and DHL, which will provide cheaper cost for a certain number of shipments for the agreed period. However, smaller or mid-scale manufacturers do not have this luxury.

    Thanks to data sharing there are more than ever data points on the way to ship goods from one place to another and also understand a cheaper way to ship the product to the end customer. There are already many companies that have started to provide data-driven logistics to small and medium scale industries.

    To save cost, the planning team also needs to become more data-aware and then find ways to implement strategies to utilize cost effect logistics.

    Photo By Chetan Arvind Patil

    Currently, the majority of the manufacturer is shipping even before understanding market needs. That also means manufacturing before capturing demand. To save cost and be more efficient demand can be re-factored by implementing just in time stocking to save cost on shipping the product earlier than required.

    Logistics data analytics just does not apply to final goods, but to also to the raw materials. This is why the scope to save costs is much broader than one can imagine. It is time manufacturers embrace data tools to provide more insights to cost savings on logistics.

    DISTRIBUTION

    Distribution is more about after-sales handling when manufactured goods have shipped out. Data in the distribution has been more critical for e-commerce where manufacturers can directly engage with customers by eliminating distributors.

    In the age of data drove process and decision making, it is more critical to understand how data allows distributors to manage inventory and tap into the next era of the supply chain. For manufacturers, the less the number of stops from the factory to end customers, the more profits they can make. For distributors to be relevant, they need to keep track of industry demand and come up with a supply chain system that provides cost-saving and at the same time real-time delivery.

    Photo By Chetan Arvind Patil

    If the customer needs the parts as soon as possible for the critical task that is stopping the production, then it becomes all about who can provide the needed goods in the fastest way possible. For such scenarios, it is important to tap into the data points in terms of usage and manufacturing.

    • From customers, distributors need to understand ways to leverage real-time usage of the parts so that they can ship when required and in some cases beforehand considering the aging the raw material has wen through.
    • From the manufacturer’s side, they need to keep track of real manufacturing throughout. This has to be the balance of demand and supply without getting into waste.

    This requires the implementation and usage of data tools that can provide distributors more than just inventory stock. There are already solutions out in the market, it is just about investing and understanding how distribution make most of the data-driven manufacturing.

    INDUSTRY 5.0

    As manufacturer look to increase the EBITDA, industry 4.0 is going to be a big driver for it by leveraging data points at each step of the manufacturing.

    Photo By Chetan Arvind Patil

    In a few years, the industry will soon transition to Industry 5.0 which will be more about smart automation with respect to decision making. These smart decisions will be towards reducing waste, enabling efficient processes hopefully without impacting human resources, and delivering what the customer needs by adapting products to their requirement.

    It is going to be a combination of Data, Connectivity, Intelligence, and Automation. May be 3D Printers are the first step towards Industry 5.0.

    PSA

    McKinsey & Company has useful resources for those interested in learning more about data enabled manufacturing.

  • PCBWay – Smart PCB Prototyping And Manufacturing

    PCBWay – Smart PCB Prototyping And Manufacturing

    Photo by PCBWay

    Developing an electronic product requires a lot of iteration. A hardware electronic device has to go through a detailed design process which is followed by numerous prototyping and evaluation. It is often a time-consuming and cost-intensive process.

    Not all the development processes happen in the house. The majority of the companies do in house designing and then rely on trusted partners to manufacture prototypes and later on the scale based on the outcome. It is critical to understand how one can design and where one can manufacture.

    MAJOR STEPS IN HARDWARE DEVELOPMENT

    There are two major steps before the hardware product hits the market: Designing and Prototyping

    Designing a hardware product for consumers requires a dedicated team that can provide proof of concept using different tools. After the idea is validated using circuit simulation tools, then the team will generate a detailed Bill of Materials (BOM) which will have all the details regarding components required to assemble and manufacture a hardware prototype in form of Printed Circuit Board (PCB). In most cases, the designing team will also provide Gerber files that will have the details of how many layers the PCB will have, which components are placed at what locations, orientation of the components, and many other assembly related details. All these technical details and information is then sent to the team which is capable of producing PCB for rapid prototyping.

    Prototyping is a very complex process and requires that the BOM being assembled adheres to industry standards. Majority of the prototyping happens using PCB which is outsourced. To assemble PCB, the service provider should have dedicated tools and teams that can take Gerber files, validate that it is correctly designed, and then process it through the manufacturing flow to provide faster PCB prototyping.

    WHERE TO MANUFACTURE

    There is no denying that China is the leader in PCB assembly with over 50% of the global market share. Shenzhen, which is often termed as The Silicon Valley of Hardware, is the go-to place when it comes to prototyping and large scale manufacturing of hardware products.

    Numerous companies provide elegant solutions in China and PCBWay is one of the leading manufacturers of PCB designing, prototype, fabrication, and assembly. It is one-stop solution for all things hardware manufacturing.

    PCBWay has opted a different approach that combines the power of software and hardware to provides manufacturing without compromising quality while ensuring timely delivery and cost effectiveness

    It is becoming a powerhouse of smart PCB prototyping and manufacturing.

    THE PROCESS

    PCBWay makes sit very easy for any customer to get started with the service. Traditional there are two types of design and development companies:

    • One which prefer to only outsource PCB and then do assembly either in a house or at other vendors
    • Second which wants everything to do done the same manufacturer: PCB, assembly, testing and scaling
    Photo By PCBWay

    For both such types of companies, PCBWay has solutions. Using PCBWay’s online quotation system designing company can opt for a quick quote. Apart from standard single-layer PCB, the company offers advanced multi-layer PCB designing and prototyping. Flexible electronics is one of the upcoming markets and PCBWay already has technology that can easily provide rapid prototyping and assembly of flexible PCB.

    All this is very handy for customers who would like to just get a quick prototype of PCB built based on the design provided, and later on, prefer to assemble somewhere else.

    If the OEM wants everything from PCB designing, manufacturing, and assembly to be done at a single location, then PCBWay already has all such resources. They can handle sample prototyping to turnkey production.

    Photo By PCBWay

    QUALITY

    It is very critical to ensure that any hardware being assembled goes through all the required quality checks. PCBWay assembly and manufacturing adhere to all such requirement that includes design rule check, automated optical inspection, electronic and probe test, automated X-Ray inspection, impedance control, RoHs lead-free, UL certification and different manufacturing tolerance.

    They have also partnered with leading design houses which ensures all these quality requirements are met from day one.

    COMMUNITY

    Apart from catering to the industry, one of the major steps PCBWay has taken is to differentiate itself from other manufacturers in China by engaging with electronic enthusiasts. They often run an online competition and PCBWay Community is one of the fastest-growing assembly communities.

    Anyone with or without knowledge about PCB manufacturing and assembly can sign up and learn rapid prototyping.

    PSA

    If you watch videos from Scotty Allen then you will definitely like below one by him on PCBWay.

  • Remote Monitoring And Management

    Remote Monitoring And Management

    Photo by Chris Liverani on Unsplash

    Monitoring of activities is not a new concept. Pre-computer era too human activities used to get monitored. With advent of high speed connectivity, monitoring has taken remote approach.

    Remote Patient Monitoring System alone is expected to be worth $1.8 Billion by 2026. Considering all possible areas which can make use of remote monitoring and management, the market size is expected to grow 10 to 100 folds. There are many areas which require remote monitoring like utilities, logistics, energy sector, weather research and many more.

    In order to understand and develop a robust Remote Monitoring And Management (RMM) solution. It is critical to capture different functions that needs to work together in order to make it more viable.

    Let us consider a practical health care solution where a patient has been released from hospital after recovering from COVID-19. With the help of RMM, a solution can be developed which ensures that if the symptoms of COVID-19 reappear on patients, then corrective actions are initiated.

    In order to build such RMM following key functions needs to to work in harmony:

    • Smart Hardware —- Data Generation And Acquisition
    • Smart Connectivity —- Data Communication And Monitoring
    • Smart Storage —- Data Storage And Access
    • Smart Software —- Data Analysis And Actions
    Photo By Chetan Arvind Patil

    Smart Hardware For Data Generation And Acquisition

    Hardware for patients RMM will require many components and the most critical are sensors. Sensors play critical role by generating and acquiring data.

    Sensors are capable of capturing activities like change in temperature, movement, heart rate, sweating, and many others. If at source the data is corrupted then any decision taken at later stage will not be accurate. Thus, it is vital to ensure that the accuracy of the sensors is within the acceptable range. Off course, there are other units like DSP, SoC, and WiFi for connectivity, which are also equally important and these come by default in any smart hardware.

    When data is captured, the next stage is to transfer it securely.

    Smart Connectivity For Data Communication And Monitoring

    As soon as the data is generated (with OR without COVID-19 symptoms) at source using smart hardware, then it needs to be transferred for long term storage and analysis. For application under study here, Bluetooth is the most practical solution due to low impact on energy consumption.

    This requires that the smart hardware with sensors is connected and is setup with mobile or desktop application. Sensor will periodically transmit the data using wireless connectivity. However, since connectivity comes with some downtime, the smart hardware will also require enough memory to store data at source. Then as soon as the connectivity is established, data can be transferred. After acknowledgement the memory from smart hardware can be cleared for future data.

    Other smart connectivity solution like WiFi, 3G, 4G and in future 5G can also find use in RMM only if the monitoring smart hardware has direct source of supply. For applications like patient monitoring, will require efficient battery management due to small form factor and thus Bluetooth is preferred compared to other.

    As a next block after the data has been transferred, it becomes important to focus on secure storage.

    Smart Storage For Data Storage And Access

    As soon as the data is available and is stored at the next immediate location (in this case a smartphone), it needs to be transmitted to a server. Once, the data reaches server then physicians can analyze and take actions.

    The critical piece here (Patient related RMM) is that when one applies technology to patients, then HIPPA comes into action. Which basically means that the data related to patients should be kept private, secure and much not be hackable.

    In order to achieve data security, as a first step end-to-end encryption is required by default. It is equally important to make the storage location secure and another layer of monitoring to capture intrusion should be implemented.

    As a final step, analysis of the data is done.

    Smart Software For Data Analysis And Actions

    It is important to understand that physicians are not data scientists. For a data scientist it is easy to play with raw data and take actions. When it comes to commercial application like the case study of patient RMM, physicians are looking for key factors related to specific disease to take corrective actions. Hence, it is important to present results such that any physician can understand it clearly.

    In most of the cases when patient RMM is developed then it is done in collaboration with physicians to ensure that the data presented follows the known medical terminologies.

    Only few of the RMM solutions will make use of existing data analytics tool in the market, but majority of the others will develop there own tools as that allows Over The Top (OTT) features that may allow other possible revenue streams.

    Take Away

    COVID-19 Patient RMM was an example on how RMM needs to be built using four key functions. Same functions can be applied to:

    • Manufacturing to track operations
    • Logistics to capture where about of goods
    • Utilities to understand consumption every second
    • Motor Vehicles to capture health of the vehicle
    • and many others.

    Many of the RMM solutions can be developed without the Smart Hardware, but only when the data to be monitored doesn’t need to be generated and is readily available.

    It will be interesting to see how RMM thrives along with Remote Working.

    Photo By Chetan Arvind Patil

    PSA

    Shirley Ryan AbilityLab in Chicago has been working closely with patients to develop many RMM. It has many useful resources for those interested in learning about RMM at the intersection of academia and industry.

  • Re-Imagining Algorithms For Outbreak Risk Management

    Re-Imagining Algorithms For Outbreak Risk Management

    Photo by Patrick Assalé on Unsplash

    In 2011, March Andreessen rightly pitched Why Software Is Eating The World. In 2018, I wrote a small note on Hardware Is Running The World. In 2020, algorithms play a crucial role in understanding and thereby catering to the needs of the world for many decades to come.

    These smart systems and context-aware algorithms are capable of capturing market trends, which has been made possible due to the amount of data that is generated every day. All these smart systems are also capable of making decisions for others and are often termed as Artificially Intelligent.

    During a COVID-19 like pandemic, AI systems could have made decisions in favor of the consumers, enterprise, and businesses. Smart systems catering to manufacturing, logistics, transport, eCommerce, and last-mile delivery would know very well that there is going to be a global demand for essential products based on the data world is sharing (as privacy is dead). That would mean more informed decisions were possible and could have driven the production and delivery of essential goods well in advance.

    Example: During COVID-19, a smart algorithm powering manufacturing industry could have projected future outcomes and provided insights to companies to ramp up the production of essential products. Which in turn could have helped adapt logistics and supply chain industry as per the needs of the cities and countries around the globe. This would have also lead to eCommerce to have enough essential products irrespective of the demand, and would have also enabled warehouses and stores to limit how many essential products a consumer is allowed to purchase well before COVID-19 hit the curve. Similar data-driven outbreak predictions can be applied to any industry, not just those producing essential products. 

    However, instead, it seems there was no projection of crises to come, and thus leading to shortage of essential products. 

    It can be questioned that outbreak based algorithms are already in place but are accessible only when one pays for it. However, given how every technological discussion is incomplete today without talking about data, isn’t it expected to have such a solution embedded in the data tools for any industry as default feature? Isn’t prediction the key for making smarter decisions?

    Focusing on the pandemic, there have been numerous attempts to make data available that could provide insight into coming epidemics:

    However, it seems with the COVID-19 crisis such data driven outbreak risk prediction solutions either failed OR were not utilized to full potential.

    Post-COVID-19, the data tool war is only going to get more intensive with the major focus on Data-Enabled Outbreak Risk Management. The important question will be whether these AI-Enabled algorithms are capable of making smart human-oriented decisions during crises.

    PSA:

    Kira Radinsky’s work on data based prediction is really interesting for anyone looking to read more technical details on prediction algorithms. She apparently wrote about importance of algorithms to predict the next outbreak in 2014.