Tag Archives: IoT

IoT For Social Good

How many times have you encountered technology in the real world, and wondered what the purpose was? It seems to have been deployed just because it could be. I know I have. The Internet of Things (IoT) can have large societal benefits, when applied purposefully. The GHC session presented by PwC strategy consultant Karla Mendez, entitled Creating Shared Value with IoT Solutions shone a light on companies who incorporate the idea of Shared Value into their technology solutions.

The idea of Shared Value is characterized by Harvard business school professors Michael E. Porter Mark R. Kramer as “a new way for companies to achieve economic success” by finding business value in social problems [1].

Business value in social problems.

Karla, who took the Shared Value course at Harvard, presented several examples of businesses using IoT to provide a societal need. When businesses position their products as providing Shared Value, a cynic can perceive this as corporate branding that hinges on pandering. Some ways that differentiate companies who have Shared Value at their core are (among other things):

  • Placing social good on par with profit as a core value
  • Make those values publicly accessible and transparent
  • Weaving those values into the thread of all aspects of operations, as an example: sourcing materials only from suppliers that align with that (social good) value

Farm in a Box

I was late to the session, so I didn’t get to hear from the presenter directly about this company. I did find them online and am glad that I did! They market themselves as an “off-grid toolkit for sustainable agriculture.” You can read more about them here. They have their sustainable development goals right on the front of their website!

Farm in a box sustainable development goals

Intelligent White Boards

An IoT enabled White Board can be deployed in classrooms, and as a teacher writes on the board, it is synced with a corresponding student display, and also allows the student to review the lessons outside of the classroom. Another added benefit is that the teacher gets real-time feedback — doing a quick pop quiz to gauge understanding, can help the teacher adjust when a given topic is not well understood and helps students stay on track for learning. This improves the quality of education. EdTech companies are on the rise, and use the data collected on improved student learning to demonstrate their value. The specific solution referenced in this example, was developed by SMART.

Smart Lighting

The value proposition for smart lighting is that if we can reduce energy use and consumption, we reduce our carbon footprint. Lighting fixtures with IoT sensors can turn off automatically, report when there is an issue (using excess energy). This also reduces energy cost. In the hospitality industry, installing IoT enabled lighting fixtures in hotel rooms can save an estimated $300 per year, per room; the same could be done with heating and cooling. One company providing IoT enabled smart lighting is the presenter’s company: PwC Connected solutions.

Homeless Tracking

There are more than half a million homeless Americans, and only 65% of them are in shelters. This leaves a quarter million people on the streets without resources. Where can IoT help? If we could assess where homeless people are in order to target locations for shelters and other resources, the government could better plan for and reduce homelessness. One solution in this space is digital kiosks. Kiosks could help homeless individuals search for and find resources, like housing. In the Phoenix area, I have seen donation meters. There was not a specific company identified as providing a solution in this space, but with a quick internet search I found that cities like New York and San Francisco are implementing innovative technology to track and align services for their homeless population. I also found an interesting article about LinkNYC, a company that converted old payphones to internet kiosks, but the results were not as rosy as originally intended.

I work for a corporation, and there is an entire branch of the company devoted to social responsibility. It is my hope that as a society, when we learn how our actions impact the world around us, we evolve the way we do business to eliminate negative impacts, not purely for the profit motive, but, because it is the right thing to do.

Recommended Reading:

A few articles I came across that show technology for societal good at work, and one illustrating the unintended consequences.

Living on the Edge

With the growing number of intelligent devices (and by “intelligent” I mean: An internet connected device running some form of software that collects and performs actions on data), bringing intelligence to the Edge has become a more pervasive topic of discussion. What is “the Edge?” Computing devices physically located at the point of use running software that is running locally instead of in the cloud. The cloud? Remotely hosted computing services such as storage (think: Google Drive) and infrastructure (virtual machines) — these services depend on a network connection. This sets the stage for the session: Developing Embedded Intelligence: Opportunities on the Edge. It was led by a panelist of experts in the field:

Brenda Zhuong of MathWorks (moderator), Miriam Leeser of Northeastern University, Micheala Blott of Xilinx Research, Mary Ann Maher of SoftMEMS LLC , and Yan Wan from the University of Texas at Arlington.

Panelists for the Embedded Intelligence session

The high level considerations that were illuminated by the panel of experts were:

  • Improving intelligence through data analytics
  • Gaining efficiency by taking advantage of the hardware capabilities
  • Reducing dependency on the (internet) network by hosting data and services where they will be used.

We then got into some real-world use cases that demonstrate the power of harnessing intelligence at the Edge.

Gain Efficiency in Embedded Intelligence; Michaela Blott

Reduce cost through custom arithmetic

Urban Aerial Vehicle (UAV)-based airborne computing for future Internet of Things; Yan Wan

UAV-based Emergency Communication

Developing an Artificial Kidney; Mary Ann Maher

Artificial Kidney


  • Seed neural networks with data coming from the actual environment so you can determine when sensors are malfunctioning — not all data is good data.
  • Understand power constraints — battery life has been a limitation
  • With all of the data being collected, privacy becomes paramount — always encrypting data at rest and in transit.

Some best practices…

If you plan to develop in this space, or are already working on a project, there are methodologies you can put into practice that will improve your solution. Here are a few:

  • There is so much sensor data, it is not possible, nor would it be advisable, to send all of it back to the cloud, which means the capability to do some level of analysis at the edge and send only the relevant data to the cloud is
  • Take advantage of cloud computing to simulate sensor data to rapidly design but then deploy at the edge.
  • Tagging quality data so you can establish a confidence in the sensor data with corresponding visualization (graphical representation) is crucial.
  • IoT devices tend not to have as much computing power, leveraging distributed computing models to perform calculations
  • Implement redundancy of sensors and computational devices in mission critical systems

Where do we go from here?

Computer vision and artificial intelligence are changing the landscape of computing. We have to improve the accuracy of vision sensors so that the data is reliable. The cost of quality vision sensors is prohibitive at the moment, and before development can really take off, it must come down. Research into correctness proofs is needed to verify algorithms developed for mission critical Edge workloads. Safety, especially for use cases like autonomous driving, is not a 90% correctness solution — it’s okay if your cell phone drops its connection, it is deadly if your car stops in the middle of an intersection. Portable IoT devices like ultrasound and water testing can bring life-saving technology to network constrained environments, and have the potential to revolutionize medicine.

The panelists were asked to make predictions for the next three years in Edge Intelligence (If any of these things come to pass, you heard it here first!) Some of them being:

  • Speech recognition as a human computer interface will become much more prevalent
  • Facial recognition will be integrated into more technology
  • Deployments of sensors and devices in rural areas will help to eradicate diseases
  • More innovative hardware platforms for IoT use cases

Recommended reading:

(IoT) Mirror, Mirror on the wall

My Grace Hopper conference schedule this year was largely driven by my interest in learning as much as I can about all things Internet of Things (IoT), retail, and edge computing. Why? I’m glad you asked! I recently joined the Internet of Things Group (IOTG) as a Software Architect in Retail, Banking, Hospitality, and Education (RBHE) <– Intel loves acronyms. I wanted to take the opportunity to learn what emerging technologies can be applied in retail settings, and understand some of the challenges that are present. My background is data center and cloud infrastructure automation, so the retail space and managing a heterogeneous set of devices with varying network architecture requires a different, or at least modified, set of tools.

My first session was titled: Mirror, Mirror on the Dressing Room Wall, What Looks Good with This Dress? Presented by Allison Youngdahl and Sunil Shettigar, of Accenture, this presentation explored how brick-and-mortar stores can improve customer experience and give better data to retailers by leveraging IoT.

We have grown accustomed to a very individualized experience online, but in real life (IRL), walking into a retail location is one size fits all. E-commerce sites track our behavior, purchasing history, make recommendations, and often have free shipping and returns to seal the deal…but, once we receive the item in hand, we’re likely to return it nearly 80% of the time. Why? Just Google “online purchase fail,” and you’ll find pages of hilarious results:

Try before you buy. Even after carefully measuring, online purchase fails are rampant

We want to touch and feel an item, in fact, shoppers who try an item in a store are seven times more likely to purchase it, so the dressing room plays a vital role in sealing the deal. Fashion designer Rebecca Minkoff leveraged technology — interactive mirrors paired with RFID tags and a video wall, in her stores to drive triple digit sales growth. So what is the architecture behind such a successful solution? Allison and Sunil presented the solution Accenture Labs partnered with the Council of Fashion Designers of America (CFDA) to build.

The Retail Interactions Platform allows retailers to:

  • Understand the customer journey as they move through the store
  • Track total number of visitors in the store
  • Track item interaction from a clothing rack
  • Determine when an item is taken to a dressing room
  • Understand how item interaction leads to a purchase at the point of sale

Underlying technology:

  • Estimote Sticker Beacons (Bluetooth proximity sensors for physical objects)
  • Business Analytics – Calculate the product engagement score
  • Video analytics – heatmaps for traffic during peak hours
  • RFID Tags
  • MAC sniffers – Raspberry Pi with a WiFi adapter
  • Data visualization dashboard hosted on Google Cloud Platform
  • RESTful APIs

Product tracking was accomplished using RFID tags to “see” how the product moves through the store. Data streams from the various sensors were aggregated using Google Cloud. To track the number and frequency of visitors, the MAC sniffer identifies the MAC address of cell phones probes, which have a unique identifier, and quantify how long the individual was in the store as well as the frequency of visits. An engagement score was determined by capturing the XYZ coordinates of the product from the Estimote beacon (was it picked up and handled? For how long?); all of this is available in a dashboard.

Retail Interactions Platform Architecture
Visitor counting with data visualization

So how does this relate to mirrors?

Dressing room ambiance — temperature, lighting, music, can change how you feel about an item of clothing. Hate harsh, unflattering lighting that accentuates all of your flaws? So do I! So how can you make dressing rooms more hospitable places? Using the platform, you now have the product location, and with additional IoT devices in the dressing room, retailers can modify the environment, and also get immediate customer feedback on a product (new size needed? A different color?) to better serve you:

Mirror, Mirror in the dressing room, give me better lighting

The final take away was that retailers should focus on customer education, entertainment, and community. As much as an e-commerce site is convenient, it can never compete with a great experience IRL.