To create an AI offering designed to help egg farms in Spain streamline a labor-intensive process, Pixelabs
needed sophisticated object recognition technology and a supportive ecosystem.
Participating in the Watson Build challenge, IBM Business Partner Pixelabs created a prototype designed to transform a time-consuming process for Spain’s egg farmers. Using an IBM® Watson® model trained to analyze images, the startup will launch an AI offering to help improve the speed and accuracy of cracked-egg detection while also driving down costs.
Deteggtor is solution to detect broken eggs. Egg farms process, package and sell hundreds of eggs per day on a daily basis. One of their main concerns about quality and food safety are based on cracked egg detection. Based on that we propose to take advantage of Watson Visual Recognition in order to help these farms to make sure they are complying with the industry regulations. After a long investigation process, we came up with a system capable to outperform current employees in this task. This way, as eggs roll over the light, any fracture even the slightest is visualized, so training an artificial intelligence to detect this fractures is achievable. Costs and time are reduced, and performance and precision are increased thanks to this system, which once trained, is a plug and play one. Therefore, farms stop to worry about selling cracked eggs. This system can process as many eggs the need, being fully scalable and replicable.
To learn more please go to IBM Pixelabs Case Study