14:33 11 May 2017
The technologies for transformative business applications are at hand. Yet many companies are slow to recognise and act on the opportunities.
The closest to an official definition comes from the Internet of Things Global Standards
Initiative:
The Internet of Things (IoT) is the network of physical objects or “things” embedded with electronics, software, sensors and network connectivity which enables these objects to collect and exchange data.
The primary driver for IoT is the broad adoption and deployment of sensors and smart devices.
Sensors are smaller, cheaper and they require less power and have more compute capacity. No longer are they limited to high capital equipment and factory infrastructure; they are literally everywhere, from the traffic signal helping to optimize traffic flow to the watch that is monitoring your vital signs. Sensors are pervasive in your everyday environment.
Pair that explosion of data generation with the commodity storage options that the cloud provides and you have all of the ingredients necessary for businesses to drive tremendous value from insights that analysis of that data can provide. Another change driving traction is the availability of technology and analytical methods that can be applied to streaming data from the sensors, data in motion. You now have the option to push decision support and performance monitoring to the edge, the source of the data. This provides expanded options for businesses to monetize the IoT.
With all this capability at hand, additional industries are starting to investigate opportunities for deploying sensors to better manage the performance of processes or machinery, as well as to track consumers’ behaviour and anticipate their needs and intentions.
Manufacturing industries, especially high volume facilities, are leveraging sensor data and advanced analytics to increase yield. Early identification of process or product variance allows early correction, resulting in reduced defects and increased efficiency. Processes that require highly variable elements such as temperature, pressure, and viscosity, or industries that require precision placement of components are benefiting from the increased density of sensors and insights generated from the data.
An industry with a history here is oil and gas, specifically production and refining. Downtime incurs huge risk and cost, so the industry continues to improve and expand how it uses sensors, networks, and analytics to generate predictive insight into the degradation of equipment performance and predict failures in oil fields, pipeline networks, and refineries. The result is expedited identification of possible equipment failures and optimization of the entire production process.
Electric utilities are expanding the use of phasor measurement unit (PMU) data outside normal operational reporting. Initially the PMU data was used to visualize and report on parameters such as voltage, current and frequency. New capabilities in streaming analytics allow them to use the data to identify events occurring within the power grid. The response to a lightning strike is quite different than a transformer failure. Being able to discern the difference in near real-time is critical to formulating and deploying a response.
Transportation is another industry leveraging IoT advancements. Heavy truck industries are using streaming data from the engines and subsystems to identify potential break-downs and then use that data to schedule efficient maintenance visits outside of operating hours. The technicians are pre-notified as to the potential problems and are equipped with the right repair parts for the quickest turn-around possible. Sensors are also deployed to the trailers or actual loads being transported. Heat, vibration, and sound frequency can all be used to monitor the safe transport of freight.
You see similar benefits in the automotive space. On-board diagnostic data is being leveraged for early detection of equipment failure, safety risks, and defects. This information can be evaluated for insight into single vehicles or across fleets. The “connected car” also provides top-line growth opportunities. The trend of integrating mobile devices with in-car infotainment systems provides endless opportunities for consumer promotion. All necessary components are in place: the customer profile, geo proximity to retail or service outlets, and the channel to deliver the message to the consumer.
To continue with the consumer promotion theme, many retailers are investing in IoT programs. In-store promotion opportunities can now be targeted to individual consumers. Advancements with beacons and in-store video tracking allow retailers to deliver targeted customer-specific messaging based on their exact location and proximity to products within the store. First the consumer opts into the retailer’s app. As the customer passes end-of-aisle displays or other areas of potential interest, the store can generate an instant promotion based on his profile and purchase history, and deliver the message or coupon to his mobile device. Real-time analytics are assessing (based on the consumer profile) what promotions to present, and at what frequency and timing, as the consumer moves through the store.
Call to Action
First, the opportunity to leverage IoT as a competitive advantage is here now, so take it. If you think you don’t have an IoT use case, you need to think harder. There are opportunities across all industries. The slow progress of others can create opportunity for your business today. But if you’re not working on IoT, you may fall behind quickly.
Second, taking advantage of IoT requires different ways of thinking – about how data is used, how much of it we can handle, how fast we can process and analyse it, and ultimately where and how decisions are made. This is not just a chance to better inform and automate business processes; it is a step change in capability that provides unprecedented opportunities in business integration and customer connection.
Third, on the technical side, the definition of “edge” is changing. Compute capacity once available on servers has moved to routers and gateways, and what used to be available on routers and gateways happens on local devices and the sensors themselves. Analytics is moving to the edge as well. You no longer need to land the data for analysis; you can now take analytics to the data, while it is in motion.
To take advantage of these trends, the technical architecture for IoT must be adaptable – at the same time that it serves the full life cycle of data, analytics, and decisions.