Farming, as a human activity, is thought to be the basis for civilisations and societies dating back 15,000 years, possibly even further back if you believe the ancient alien astronaut theory. In fact, ancient alien astronauts from the Anunnaki race are thought to have introduced Earthlings to farming in the first place, and gifted humans the plough. Whatever its age, farming is still a globally widespread activity today. Indeed, until around 50 years ago, the vast majority of countries around the world were agrarian, meaning their economies and societies were reliant on the income generated by the agricultural sector – not just the food produced by it. Even today, the largest economy in the world – the US – is also the world's largest exporter of food.
Connecterra, a Dutch sensor hardware and machine learning firm based in Amsterdam, Netherland, has used motion sensors and AI tools with the aim of studying cow's behavior. The company's "The Intelligent Dairy Farmer's Assistant" is now in the US following effective deployment in European countries for many years. The AI program works on data collected from motion sensors fixed on the animal's neck to study its activity. The inputs, when associated repetitively with practical data about the cow's behavior, allows the Intelligent Dairy Farmer's Assistant to tell from just data about the needs of the animal. Using such data, it will be easy to tell when a cow has become sick or is ready for mating.
At the Computing Conference 2018: Shanghai Summit on June 7, Alibaba Cloud introduced its ET Agricultural Brain that aims to lower pigs' death rate by 3% and allow each sow to raise three more piglets each year. According to its President, Simon Hu, ET Agricultural Brain can monitor each pig's daily activity, growth indicators and other health indexes using AI technologies such as visual recognition, voice recognition, and real-time environmental parameter monitoring. Hu said that active pigs will become favored over heavier ones: a pig that runs 200 km over the course of its life will be sold over a 100 kg one. Sharing his company's experiences using ET Agricultural Brain at the conference, Sichuan-based pig farming enterprise Tequ Group's Chairman Wang Degen said that Alibaba Cloud's technology and ecosystem integrates cutting edge interactive automation with hog farming. Other early adopters include the Shaanxi-based agricultural company Haisheng Group, which according to Alibaba Cloud's estimation, could save around USD 3.1M in annual operating costs by using the technology.
Artificial intelligence is the beating heart at the center of delivery robots, autonomous cars, and, as it turns out, ocean ecology trackers. In a blog post on Friday, Global Fishing Watch, a platform founded by Google, Skytruth, and Oceana that monitors fishing activity around the globe, announced the addition of two new data layers to increase "transparency" and "awareness" around overfishing. One of the new layers tracks transshipment, a method whereby one fishing vessel offloads its catch to another, refrigerated ship at sea. It's often used to combine illicitly caught fish with legal seafood, and it usually takes place in international waters, making it difficult for authorities to track. Working from a database of 300,000 ships across 12 categories, Global Fishing Watch trained machine learning algorithms to identify when a fishing vessel is docked alongside a refrigerator vessel, and to determine the likelihood that transshipment is taking place.
India's Mahindra & Mahindra, one of the biggest suppliers of smaller tractors to the U.S., and other manufacturers are racing to develop what they see as the future of farming: robo-tractors and other farming equipment to help produce more food, more sustainably at a lower cost. John Deere has tractors and combines on the market that free the driver in the cabin from the actual driving so he or she can monitor the crops and adjust pesticide, water and soil levels. Technology from Agco Corp.'s Fendt lets several driverless tractors follow a lead tractor driven by a human. Japanese firms Kubota and Yanmar are planning to launch driverless tractors that they expect to be popular with elderly farmers. The next generation is tractors that can drive entirely by themselves.
In a paper from California Institute of Technology's Jet Propulsion Laboratory, the author laments the loss of connection between machine learning and solving real-world problems. The main question that seems to come up is: what good can machine learning or artificial intelligence (AI) do? A lot, as it turns out. AI could play a big role in aiding and even solving the issues of world hunger and poverty in ways that are surprisingly simple, but increasingly necessary. When you think of AI, it's possible that fixing world hunger isn't the first application that comes to mind.
A slew of AI weed killers are on the horizon and have the potential to disrupt the multibillion dollar pesticides business. Among them is Swiss-company ecoRobotix and its weed-killing robot. It's solar-powered and can kill weeds for 12 hours straight without an operator at the helm. EcoRobotix uses 20 times less herbicide than traditional methods that spray entire fields. Founded in 2011, ecoRobotix develops autonomous weeding robots, which help farmers to produce healthier food with a more efficient and sustainable use of herbicides.
From a first-principles perspective, the task of feeding eight billion people boils down to converting energy from the sun into chemical energy in our bodies. Traditionally, solar energy is converted by photosynthesis into carbohydrates in plants (i.e., biomass), which are either eaten by the vegans amongst us, or fed to animals, for those with a carnivorous preference. Today, the process of feeding humanity is extremely inefficient. If we could radically reinvent what we eat, and how we create that food, what might you imagine that "future of food" would look like? The average American meal travels over 1,500 miles from farm to table.
This collaboration will help import field boundaries from Operations Centre to organize fields for drone flights, order on-demand high resolution drone imagery, and receive processed or raw data for decision making during the growing season. In 2017, Deveron completed over 2200 flights for its customers. "As we continue to expand our drone fleet in North America, we look forward to growing our user base and offering farmers a solution that allows them to focus on farming, not flying drones and processing data," says David MacMillan, President and CEO of Deveron.