Integrating artificial intelligence into your IoT solutions

In this article, you learn how to use artificial intelligence, or at least machine learning, to raise the alarm when there are changes in a supposedly static environment, such as a hay barn while the hay is drying after the harvest. I use two methods to achieve this: visual recognition and image comparison. Visual recognition requires more processing than can be done easily on a Raspberry Pi. The solution here is to upload pictures of the IBM Cloud, and ask IBM Watson Visual Recognition to identify the objects in them. If a new object appears, or if an expected object disappears (and doesn't show for a whole day, because objects may only be identifiable under certain lightening conditions), this AI system raises an alarm. Because object recognition using IBM Watson Visual Recognition requires significant bandwidth to upload pictures to the IBM Cloud, I designed an AI system that can work on a low-bandwidth network connection, such as a LoRa connection. To detect changes in such an environment, the second part of this article uses image comparison. Images are taken every ten minutes, and each time the image is compared to the image taken 24 hours prior. This way, the changes in lightening conditions will hopefully be minor enough to prevent false alarms. To implement visual recognition in the cloud, we will base our architecture on the short range architecture in the first article. The devices in the hay barn use WiFi to communicate with an access point in the farmhouse which is connected to the Internet.