What do queues, zoos, and machine learning have in common? Watson IoT, of course! Marwell Zoo is building better beds for their animals with IoT and machine learning. Using Watson IoT Platform, the park’s keepers are working in tandem with IBM, designing a better way to reduce energy consumption. All while creating a more comfortable environment for the animals.
Can machine learning be used to create better conditions for animals at Marwell Zoo? The question first emerged after Andy Stanford-Clark, CTO for IBM UK & Ireland, presented an introduction to Internet of Things at a UK Chamber of Commerce conference in February 2017.
Marwell Zoo is dedicated to the conservation of wildlife and other natural resources. The zoo aims to conserve species and their habitats, locally and globally, and advocates environmental and social responsibility in support of these goals. For these reasons, the Marwell sustainability team have embarked on a quest to improve the sleeping conditions for the animals. They want to provide the animals with more comfortable housing, while reducing energy consumption and cutting heating costs – without compromising habitat quality.
It is this recent project in Munich that Andy latched on to when Marwell Zoo contacted him. To make a portable version of the coffee queue monitoring system, Andy installed one of the thermal sensors, connected to an ESP-8266 Arduino-compatible microprocessor, in a small 3D-printed plastic box. This was connected to a Raspberry Pi using a micro-USB cable, and he used the 8×8 grid of LEDs on a SenseHAT add-on board on the Pi as a display. A Node-RED application running on the Raspberry Pi displays the 16 temperatures readings being detected by the thermal sensor as a heat map, updating once a second.
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