What do shark recognition, gunfire detection, and bike sharing have in common?

Artificial Intelligence and Internet of Things perspective. Whether or not data coming from everyday life objects offers great importance and value is a good question. How do you make the best of it? Who can make the best of it?

“Connected’ does NOT necessarily mean smart.” — Bill Schmarzo

Three examples can be given for illustration. One in China, related to the bike sharing sector, one in the USA within urban lighting market, and the last one in Australia in the area of shark detection.

In China, the oFo bike app provides you with the code to unlock a shared bike and handle the payment process. That helps to answer the questions: How many people use the bikes? Where do most people take or drop bikes off? In the same way as oFo’s people use the data to optimize their distribution plans, the data is gold for city officials in order for them to plan the design of their urban architecture: roads, bus lanes, cycle lanes, walkways etc.

In California, GE is working with ShotSpotter, which is designed for detecting and locating gunfire in real time. Teaming up with Intel and AT&T, GE is combining cameras, microphones, and sensors into its intelligent LED streetlights. GE is then upgrading its urban lights far beyond simple illuminating capabilities. While today, ShotSpotter is using complex real-time algorithms and the work of a team of human specialists, the data collected by IoT in real time can be associated with available historical data to be processed by Deep Learning for further automation.

In Australia, the University of Technology Sydney (UTS) is harnessing Deep Learning and Artificial Intelligence algorithms to detect sharks from drone footage. First, they preprocess public videos of sharks. This is the learning part. Then, a Neural Network runs detection and recognition algorithms. Empowering the action of drones, this provides a real-time search and rescue service.

Want to take an in-depth look at the state of AI and IoT and to explore how these technologies synergize with each other and what to expect in the future? Take some time to read my last DZone article “AI and IoT: Taking Data Insight to Action” here.

One more thing… Don’t anthropomorphize AI’s, they hate that.