Food
Machine learning
Life on Earth
Governance
Economic Growth
General Rights
Sustainable Cities
Inequality
Right of food:
have regular, permanent and unrestricted access to quantitatively and qualitatively adequate and sufficient food
Malnutrition
Hunger
Smart agriculture and food systems
Reduce waste
Forecast drought and hard times
Across the globe, communities at every scale have recognised the key role food can play in dealing with some of today’s most pressing social, economic and environmental challenges and are taking a joined up approach to transforming their food culture and food system.
Foodtech can be described as the intersection between food and technology; the application of technology to improve agriculture and food production, the supply chain and the distribution
Unrelated
Machine learning is really good at telling Yes or No at questions
http://blogs.worldbank.org/sustainablecities/taxonomy/term/16055
FlavorDB
Database containing a whole lot of food with their Taste
ML to solve food hunger
Environmental impact of Food in the World
Efsa: European food safety autority
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food insecurity
- Smart agriculture and food systems
AI-augmented agriculture involves automated data collection, decision-making and corrective actions via robotics to allow early detection of crop diseases and issues, to provide timed nutrition to livestock, and generally to optimise agricultural inputs and returns based on supply and demand. This promises to increase the resource efficiency of the agriculture industry, lowering the use of water, fertilisers and pesticides which cause damage to important ecosystems, and increase resilience to climate extremes.
The need of enough local food available everywhere
Is a condition that results from eating a diet in which one or more nutrients are either not enough or are too much
food needs to satisfy the dietary needs of every individual
ML
Being without sufficient quantity of food
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11 Data intelligence for better food inspection to decrease or eliminate claims that are a major source of food waste and improve early warning systems for post-harvest plant disease and pest outbreaks
Fresh products are inspected to see if they fit specifications at every step of the supply chain. The inspection process is usually fairly manual and therefore time consuming and subjective. Automated food inspection process via machine learning could significantly reduce errors and ultimately reduce food waste as less shipments would be refused and wasted. Different data can be used to feed the machine learning models and include images taken by a mobile phone (AgShift), hyperspectral images (Impact Vision) and sensor data.
Better data collection and analysis could also significantly improve early warning systems for post-harvest plant disease and pest outbreaks. Data that could be used for such systems include satellites,hyperspectral images and sensors. An example of such solution is Agroshield by Saillog that notifies subscribers after crop diseases and pests were detected on nearby farms
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14 Farm to fork digital marketplaces to prevent waste and energy consumption during transports
By directly connecting farmers and end buyers locally, waste happening due to inefficient supply chains can be avoided.
The eat-local movement mostly drives the emergence of such models in richer countries while the potential for more efficient and timely supply chain is the main factor for adoption in emerging countries.
Platforms targeting emerging countries like M-Farm might be therefore more impactful.
Some startups in the space in developed countries include Farmigo that uses a just-in-time model, where producers only harvest food that has already been ordered on Farmigo or La Ruche qui dit Oui that allow users to group themselves to buy directly from their local farmers.