The Internet of Things – The Tipping Point

The Internet of Things (IoT) is predicted to reach a tipping point in 2013. Mobile, Cloud, Big Data and Social are converging to enable countless applications of IoT in the future – and of all the disruptors in play today, IoT could very well be the biggest. With IoT, objects use tiny devices to make them identifiable by their own unique IP address. These devices can then autonomously communicate with one another. In evaluating the many IoT applications, I have categorized the path forward into four buckets: Smart Products, Smart Optimization, Smart Automation, and Smart Decisions. Here are examples across each category. 

Smart Products

From a market perspective, companies will create an ecosystem that delivers intelligent products to enable new business models and revenue streams. Beyond the objects and sensors, true value will depend on software, services, and analytics. The mountain of resulting sensor data represents a big IoT challenge, as will ecosystem development and management. Examples of smart products are:

  • Connected thermostats that allow you to remotely manage it from your device
  • Utility meters that collect information without human help
  • Refrigerators connected to the Internet that order food when items are running low
  • Smart objects (lamps, fridges, ovens, etc.) that use Facebook-like interfaces to deliver detailed messages or instructions
  • A car that reads your text messages to you as you are driving, warns of bad drivers nearby by computing a score in real time, or warns of a low battery through a social network
  • Vending machines that use cameras and video analytics to change the selections based on the demographic of the individual(s) standing in front of the machine
  • A connected toothbrush that monitors brushing and provides feedback on pressure, angle, location and length of brushing, while monitoring itself for brush life and battery strength
  • A bathroom scale with an ecosystem of more than 30 apps that turn data into diet and health solutions
  • A smart Fork that measures the length of time between your bites, and vibrating if you shovel the food in too quickly
  • Devices that allow doctors to collect information from patients remotely and be alerted whenever there is a problem.
  • Prescription-medicine bottles that call when you forget to take your pills
  • Sensors that allow a home owner to see the person ringing their doorbell on their smartphones

Smart Optimization

While Smart Products promise to introduce new innovations and revenue streams, Smart optimization focuses on effectiveness and next generation efficiency. Sensors, sensor data, and prescriptive analytics will usher in a new era of optimization. Examples include:

  • Wiring delivery trucks with sensors that monitor driving distances and times, track truck locations, and assess driving habits
  • Social networks of machines (i.e. a jet engine or a power turbine) and humans. A real-world example from GE where the machine continually posts its real-time performance information to the appropriate engineers, creating a collaborative network of machines and humans. With $284 billion in annual airline industry waste driven by fuel inefficiency, unscheduled aircraft maintenance, and delayed flights, GE sees an opportunity for optimization. A one percent improvement in aircraft engine maintenance efficiency can reduce related costs by $250 million annually. A similar one percent fuel savings in power generation could add more than $4 billion annually to the global economy
  • Rolls-Royce provides an example of preventive maintenance and fault prevention by relying on the components within their engines to provide information like usage and how parts are wearing. It then schedules the appropriate servicing
  • The CDC estimated hundreds of thousands of vaccine doses are thrown out each year because of poor refrigeration at clinics, hospitals and doctors’ offices. With barcodes, RFID and sensors, real-time temperature monitoring could be made automatic and save billions
  • With real-time location solutions, organizations can hone in on very specific recalled items ( including food, drugs and parts) that may be at issue, and send automatic mobile alerts to organizations and consumers, reducing inventory loss, saving money and helping quickly redeem consumer or business trust
  • With sensors monitoring the temperature of fruits and vegetables, a truck full of produce that is about to spoil can send real-time alerts to the food distributor about the condition, and re-route the truck to a different location if needed
  • At a giant concrete pour in a large industrial project, rather than flying blind, or having to stop the pour to test the many variables that exist in concrete, companies can simply embed a mesh of disposable sensors in with the pour, and monitor these sensors for various parameters
  • By combining data from automobile sensors with weather readings and traffic data, insurance companies can gain a better situational understanding of the conditions surrounding a claim
  • Dutch company Dyzle uses Tags with connectivity to monitor key parameters of medicines or food while they are in transport or cold storage, to ensure that they do not deviate outside a specified temperature range stipulated by a company’s quality requirements as well as regulatory requirements – and patient/consumer safety expectations 

Smart Automation

Smart automation is poised to contribute to next generation efficiency as well – but at a price. Automation continues to be the single biggest impact to middle class jobs, and smart automation makes this issue more acute. A great case was made for this in a recent article titled: Practically human: Can smart machines do your job? The article provides several great examples:

  • Driverless cars – Google’s automated car drives itself by using Google’s vast collection of maps and information from special sensors to negotiate traffic. Driverless cars will have a revolutionary impact on traffic one day — and the job market. In the United States alone, 3.1 million people drive trucks for a living, 573,000 drive buses, 342,000 drive taxis or limousines. All those jobs will be threatened by automated vehicles.
  • BookBots retrieve books in libraries when students request them instead of humans. With customers scanning books themselves, one library is processing more books than ever while shaving 15 percent from staff hours by using fewer part-time workers
  • Need an Assistant? Microsoft has unveiled a system that can translate what you say into Mandarin and play it back – in your voice. The Google Now personal assistant can tell you if there are traffic jams on your regular route home and suggest an alternative. Talk to Apple’s Siri and she can reschedule an appointment
  • Smart banking: In South Korea, Standard Chartered is expanding branches that employ a staff of three, versus an average of eight in traditional branches. They’ve replaced a dozen full-service branches with smart branches, and expect to have 30 more by the end of this year. Customers do most of their banking on computer screens, and connect with specialists elsewhere by video-conference if they need help
  • Driverless train system: The British-Australian mining giant Rio Tinto is investing $518 million in the world’s first long-haul, heavy-duty driverless train system at its mines in Western Australia
  • 3D printing: a furniture-making company in the Netherlands needs only a skeleton crew of four people. The hard work at the Eindhoven-based company is carried out by an old industrial robot that was fashioned into a 3D printer
  • A pilotless airliner: James Albaugh, retired CEO of Boeing Commercial Airlines said in 2011 that a pilotless airliner is going to come; it’s just a question of when. “You’ll see it in freighters first, over water probably, landing very close to the shore” 

Smart Decisions

Perhaps the most valuable of them all is Smart Decisions. Sensor data will combine with other sources of data – including social – to optimize decision making. I see this category as the most challenging. Each category has a deep analytic component, which in affect drives Smart Decisions. Listening and sensing, fusing sensor data with other sources, finding the insight through the noise and ultimately responding is wrought with complexity. The sense and respond nature of the Smart environment requires an insight-to-action framework that creates a blueprint for Smart Decisions.   

The Internet of Things promises to usher in the next generation of efficiency and a level of effectiveness we have yet to discover – many believe we have reached the tipping point. What do you think?

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