DZone Research: IoT Use Cases

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DZone Research: IoT Use Cases

There is tremendous diversity in IoT use cases.

· IoT Zone ·
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To understand the current and future state of IoT, we spoke to more than a dozen IT executives active in the space. Here's what they told us when we asked, "What are a couple of IoT use cases you'd like to highlight?":

  • 1) Home automation: connects devices securely to a hub or mobile app, allowing users to remotely control and monitor smart devices in their home. Example customers – INSTEON, August Locks, Vivint. 2) Agriculture: stream readings from thousands of sensors in the field, and intelligently adjust farming based on those readings. Example customers – Climate Corp, Rachio. 3) Delivery and Fulfillment: track trucks and inventory in the field, stream status to a central administrative dashboard, and trigger alerts to end users and customers. Example customers – Gojek, iCabbi.
  • 1) Automotive manufacturing simulation loop for each vehicle to improve features under vehicle development analysis. Feedback from driver and metrics from the car — seat warmers and an automatic door opening. 2) Oil and gas stations use petroleum refinery analysis to determine the cleanliness of the fuel.
  • 3M smart filters. Filter tell you and tie into Amazon dash. Reinforces frequency. Go about life and let sensor determine when reaching suboptimal levels.
  • Take care of people’s environments to make them healthy and more comfortable. Make the environment visible. Trigger responses to help make healthy – turn on purifiers, close windows, adjust temperature, monitor CO2. Optimize for what you are doing.
  • 1) Komatsu uses data from machines to improve the performance of machines as well as throughput from the operators. Predictive maintenance, performance, redesign based on consumer use of the devices. Drillers moving deeper versus horizontally. Each machine is an individual. Models that are generally applicable but customized based on location. Feature engineering for better products and models that fit well. There is a cycle of continuous improvement. ML models have to be able to beat the human.
  • Smart manufacturing and energy companies implementing a hybrid model for different factories all over the world with centralized operations, as well as operations at a local level. Security constraints with limited connections need special configuration. POCs connecting different machinery that calibrates sensors or pieces of devices. Add more data sources and compute on the edge. This facilitates self-independently run factory operations. Deploy just enough intelligence at the edge to improve factory processes. This validates having an open model and open standards to meet the interoperability needs with the right support for a commercial enterprise.
  • 1) A generic problem with IoT and consumer appliances is knowing how long they are going to work. It works by talking to the device, app, and cloud, but what happens when the cloud service goes away? This limits the overall available market. How to make sure they continue working on your home? Having a LAN in your home is a huge use case. Even if cloud service goes away you can continue to have and control the device from your LAN. 2) Now we have companies providing device plus cloud service plus the app – cloud to cloud interoperability. Get to the place where you have a manufacturer who provides the device and then connects to the cloud you want with an OCF connection or account. This enables a whole sector of manufacturers who are not able to provide cloud service. The same principle as having a single dashboard to manage the platform applies to manage security. A thorough security model is defined in OCF – different privileges for different users – works the same regardless of manufacturer or device.
  • Smart appliances — notifications on inventory. Autonomous vehicles — traffic avoidance and driving.
  • 12 to 20 percent utility spend reduction. We're able to handle the technical side variability of deployments from 50,000 sq. ft. to 1 million sq. ft. Integrate with different solution providers and handle the variability. Deliver value quickly. Self-installation approach. Deployed and up and running in hours. Run tests for self-installation kits in under 10 minutes.
  • 1) Several plastics factories have approached us to solve problems at their plants. One needs to automate the collection of temperature and pressure readings from multiple water tanks—a critical component in their process as cold water is used to set newly molded plastic. Another is looking to automate the counting of cycles on their plastic injection molding machines. In both of these cases, our solution provides a working solution with barely any disruption to an existing operation and without requiring the companies to purchase expensive new equipment. 2) We’re also currently working with a major city on upgrading maintenance systems in a historic building complex. They need data about their water pump systems and elevators to better serve their tenants. Our solution connects and programs the controllers on the pumps and new sensors on the elevators. Even though the pumps and elevators in the complex vary in age and model, we connect them all together into a common system that presents historical operational data on live dashboards, issues alerts when readings are off, and predicts future problems detected by ML models.
  • 1) Preventing floods during storms — Opti is working to create what they call “The Internet of Stormwater” — a smart stormwater management system that proactively monitors weather forecasts and actuates valves to minimize flooding and environmentally hazardous run-off. With Particle as the engine of their connectivity, Opti now boasts over 130 installations of their platform across the United States. Their steadily-growing customer base includes major cities such as Kansas City, MO, Philadelphia, and Albany, as well as private enterprises. Opti’s CMAC system is already proving invaluable for those communities. In Ormond Beach, Florida, for example, Opti’s CMAC system greatly mitigated the effects of 2017’s Hurricane Irma. 2) Detecting ocean water quality with the “Smartfin,” it’s a green IoT initiative from the Scripps Institution of Oceanography, Surfrider Foundation, and Lost Bird 9. It’s easy to upcycle any typical surfboard with Smartfin, turning everyone who uses it into a source of valuable oceanic data collection. The IoT-enabled fin contains environmental sensors that gather data on near-shore ocean chemistry. By working with both the scientific and watersports communities, Smartfin is helping to demystify the secrets of the sea, and providing the world’s policymakers with the insights they need to make more informed environmental decisions.
  • 1) One use case for our in-memory computing platform is in smart city IoT applications. Leading IoT platform providers have integrated our solution into their platform to provide the speed and scalability needed to ingest, process, analyze and respond to data generated by millions of endpoints included power meters, street lights, and more. 2) Another frequent use case is for powering massively scalable, high-performance core banking platforms. These platforms must be able to process thousands of transactions per second to support the massive increase in transactions that resulted from mobile banking. Hundreds of millions of mobile phones — IoT devices — are now endpoints for massive mobile banking applications.

Here’s who we spoke to:

automation, connected devices, iot, manufacturing, predictions, smart appliances, smart homes

Opinions expressed by DZone contributors are their own.

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