Eye on AI - September 6th, 2019
Welcome to Aigora's "Eye on AI" series, where we round up exciting news at the intersection of consumer science and artificial intelligence!
This week, we’ll be expanding the conversation on AI and food by discussing how companies have begun using machine learning to assist in food safety and reduce waste.
FDA Using Machine Learning to Prevent Food Supply Contamination
We begin with an article out of GovernmentCIO, titled “Machine Learning Text Analytics Aid Food Safety,”describing how a new FDA’s Center for Food Safety and Applied Nutrition project, called ‘Emerging Chemical Hazard Intelligence Platform,’ is using automated data analytics to anticipate chemicals that might lead to adverse health events.
“Instead of reacting to regulated chemical outbreaks after they occur,” writes author Faith Ryan; “the center adopted its intelligence platform to anticipate through text analytics to discover chemical risks earlier in the signal lifecycle and to better manage potentially harmful public health events.”
Most of the data streams pulled were text-based, things like current events, news articles about chemical spills, or scientific journal articles that at first glance may seem unrelated. But once predictive analytic results are compiled, patterns are identified that are simpler to understand — it’s the combination of text analytics paired with machine learning that makes the technology so appealing.
This new machine-learning project helped FDA officials reduced time-consuming processes and make better informed decisions, with many similar applications on the horizon.
Food Waste AI Camera Provides Optimism for UN Sustainability Goals
Next up, a story about how an AI-camera is helping save millions of meals per year from the waste bin. In an article out Gulf News, article titled “UAE commercial kitchens use Artificial Intelligence to track food waste,” staff reporter Faisal Masudi describes how the unveiling of a AI-powered camera at an event in Dubai, called ‘Winnow Vision,’could reshape global sustainability by preventing unnecessary food waste.
“A camera is fixed on the wall, overlooking the bin,” continues Masudi. “As a food item is thrown in, the camera recognises the item. Staff can confirm or reject, on a touchscreen, what the camera says it saw go in. As more image data is gathered, Winnow Vision becomes smarter. When recognition capability is turned on, a state of semi-automation is reached where users are only required to confirm the suggested food. This reduces human error and saves users time.”
Fifty of UAE’s (United Arab Emirates) largest kitchens have signed up for ‘Winnow Vision,’ with many representatives from UAE-based hospitality companies signing on to the ‘UAE Food Waste Pledge’ at the conference, pledging to save millions of meals over 2019 and 2020. Dr. Al Zeyoudi, the Minister of Climate Change and Environment for the United Arab Emirates, took the opportunity to reaffirm the UAE’s commitment to meet the United Nations’ Sustainable Development Goal to cut food loss and waste 50 per cent by 2030.
“The fast pace of technological advancement brings us a wealth of innovations that we can leverage to drive our sustainability agenda forward,” continues Zeyoudi. “Employing artificial intelligence as a powerful tool to manage and eliminate food waste adds significant momentum to our efforts and makes our task that much easier and more seamless. Efficient collaboration between hospitality and tech companies will inform food waste management decisions and deliver substantial benefits.”
AI’s continued development in food production, and the creativity many companies like the FDA and UAE bring to its use in addressing global sustainability issues, provides optimism for the future of the food industry and the benefits of AI and machine learning. Expect to see wider scale AI implementations similar to these soon.
Advances in New technologies and Retail:
Advances in Precision Farming:
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