This DIY smart chicken coop features AI-based predator detection

Raising chickens can be a very rewarding endeavor, as they can provide fresh daily eggs and help get rid of pests in the yard. But, like all animals, they require care. Most importantly, you’ll need to ensure that they have regular food and water, and you’ll need to protect them from predators like coyotes, foxes, […]

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Raising chickens can be a very rewarding endeavor, as they can provide fresh daily eggs and help get rid of pests in the yard. But, like all animals, they require care. Most importantly, you’ll need to ensure that they have regular food and water, and you’ll need to protect them from predators like coyotes, foxes, and cats. To ease the workload, you may want to consider building Coders Cafe’s DIY smart chicken coop that features AI-based predator detection.

The purpose of a coop, aside from being a comfy place for chickens to roost, is to provide protection from weather and predators. This design is pretty small and is probably only suitable for one or two chickens, but the concepts can be applied to larger coops. It provides a few very useful features: remote or automated feeding, remote or automated door operation, and predator detection with remote notifications. You’ll never have to worry that you forgot to feed the chickens or that you left the door open, and you can respond immediately if you get a notification about a predator.

An Arduino UNO R4 WiFi board oversees those features, operating the door and dispensing food using simple motor-driven mechanisms. A companion app lets the user set an automated door and food schedule, or perform those actions with the tap of the button. A Twilio app integration enables SMS alerts.

The predator-detecting magic works thanks to DFRobot’s HuskyLens AI camera sensor. Users can train that to recognize specific predators and then it will tell the Arduino if it sees one. That communication occurs over I2C and is easy to setup, removing all of the difficulty of implementing AI. 

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Reimagining the chicken coop with predator detection, Wi-Fi control, and more

The traditional backyard chicken coop is a very simple structure that typically consists of a nesting area, an egg-retrieval panel, and a way to provide food and water as needed. Realizing that some aspects of raising chickens are too labor-intensive, the Coders Cafe crew decided to automate most of the daily care process by bringing […]

The post Reimagining the chicken coop with predator detection, Wi-Fi control, and more appeared first on Arduino Blog.

The traditional backyard chicken coop is a very simple structure that typically consists of a nesting area, an egg-retrieval panel, and a way to provide food and water as needed. Realizing that some aspects of raising chickens are too labor-intensive, the Coders Cafe crew decided to automate most of the daily care process by bringing some IoT smarts to the traditional hen house.

Controlled and actuated by an Arduino UNO R4 WiFi and a stepper motor, respectively, the front door of the coop relies on a rack-and-pinion mechanism to quickly open or close at the scheduled times. After the chickens have entered the coop to rest or lay eggs, they can be fed using a pair of fully-automatic dispensers. Each one is a hopper with a screw at the bottom which pulls in the food with the help of gravity and gently distributes it onto the ground. And similar to the door, feeding chickens can be scheduled in advance through the team’s custom app and the UNO R4’s integrated Wi-Fi chipset.

The last and most advanced feature is the AI predator detection system. Thanks to a DFRobot HuskeyLens vision module and its built-in training process, images of predatory animals can be captured and leveraged to train the HuskyLens for when to generate an alert. Once an animal has been detected, it tells the UNO R4 over I2C, which in turn, sends an SMS message via Twilio.

More details about the project can be found in Coders Cafe’s Instructables writeup.

The post Reimagining the chicken coop with predator detection, Wi-Fi control, and more appeared first on Arduino Blog.