The Internet of Things (IoT) has the potential to connect trillions of devices, but the cost and complexity of adding sensors and connectivity to traditional “dumb” devices can be prohibitive. This has led to a “long tail” of devices that have yet to be connected to the IoT. However, smart cameras and cloud-based AI platforms may provide a solution to this problem.
Sensor fusion is the foundation of using AI in the IoT. It allows for greater insights by using multiple sources of data at once. Most sensors only detect one property and must be deeply integrated into the application. However, image sensors, or cameras, can capture data without being deeply integrated and can be deployed long after the application is in the field.
Smart cameras that use AI can monitor, identify, and recognize objects and events, and automatically generate actions. This allows for a non-intrusive form of sensing that is not tied to any single parameter. The RSL10 Smart Shot Camera platform from onsemi is an example of a smart camera that can be integrated into a cloud-based platform with AI capabilities like IoTConnect from Avnet.
Smart cameras can be used for a variety of applications, including asset tracking, stock monitoring, HMI monitoring, hazard detection, traffic monitoring, environmental monitoring, and proximity detection. The use of smart cameras in these applications can reduce the cost and complexity of traditional sensor modalities.
The continued improvements in cloud-based AI will also play a crucial role in the expansion of the IoT. As billions of devices go into service, AI will be the only practical way to process the huge amounts of data being captured by all types of smart sensors. Systems deployed today that use cloud-based AI will get smarter over time, without the need for any changes in the field.
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