6 social entrepreneurs helping build a better tomorrow


The UN's Sustainable Development Goals are a set of 17 objectives to tackle global issues like hunger, joblessness, poverty, climate change, and food waste, among others. Long term, Carroll envisions a world in which Skycision can help tackle macro issues affecting global food security. Womensphere has five cornerstone initiatives: Leveraging technology and media to educate and empower; developing programs to unleash women's potential; advancing the next generation of women leaders; mobilizing the global community; and recognizing world-changing innovators at the Womensphere Global Awards. The Ocean Cleanup, founded by Slat in 2013, is a pollution collection system driven by ocean currents.

AI for Good: How advanced crop intelligence can help solve food production challenges


By being more effective in how they target crops, growers expe rience the economic benefits of reduced costs for crop protection, reduced crop threats, and therefore increased yields. Gamaya's precision agriculture services equip growers with information about the location, type, and intensity of the weeds infesting their fields. Targeted spraying reduces chemical usage, thereby significantly reducing the farm er's costs, lowering the negative impacts to the environment, and on human health, and likely slows the spread of herbicide-resistance. Not only is the cam era itself small, but it compresses data 100 times more efficiently than other hyperspectral cam eras, making our data processing quicker, less complex, and less expensive than with other hyperspectral sensors.

8 Disruptive Digital Technologies... with the Power to Transform Agriculture


Drones are being used in soil and field analysis, planting, crop spraying/monitoring, irrigation and crop health assessment (as in this one minute video, demonstrating how a drone can be used to observe the impact of a crop feeding program). Syngenta and DuPont Pioneer both have made the foray into drone technology to assist farmers in making fertilizer application and irrigation decisions through aerial images. An exciting example in agriculture is machine vision, where computers process visual data collected via UAV, satellite or even smart phones and provide the farmer with useful information. A likely early use of VR is livestock video monitoring systems that send data back to a computer program, which in turn constructs a visual representation of the herd or brood allowing the farmer to check in on the cows or chickens remotely.

Solving The Bee Crisis with Machine Learning Big Cloud Recruitment


Without the natural pollination bees provide, global food supply would deplete so rapidly, the effects would be disastrous. And what is Big Data and Artificial Intelligence doing to stop numbers from further decline? Monitoring bees movements in accordance with their environment, the Bee Smart device allows beekeepers to remotely monitor their hives. As the world faces many challenges, start-ups like the ones above are investing in making the world a better place for everyone by using big data, machine learning, and artificial intelligence.

Image analysis and artificial intelligence will change dairy farming: Cow gait images allow early detection of serious diseases


Methods for finding lameness by detecting back arch had been studied; however, that method was effective in detecting moderate to severe lameness. This group established a method for the early detection of lameness from cow gait images with an accuracy of 99% or higher by using their own human gait analysis technique. Based on the large number of cow gait images taken by this sensor, this group characterized cow gaits, detecting cows with lameness through machine learning. He continues, saying, "By finely adjusting the amount of expressed milk and the amount of feed as well as by showing farmers cow conditions in detail through automatic analysis of cow conditions, we can realize a new era of dairy farming in which farmers can focus entirely on health management of their cows and delivering high-quality dairy products."

UAV-based crop and weed classification for future farming


Modern approaches as agriculture system management and smart farming typically require detailed knowledge about the current field status. We use a comparably cheap, out-of-the-box UAV system to capture images of a field and compute a class label to each pixel, i.e., determine if that pixel belongs a crop or a weed. We address the problem of analyzing UAV imagery to inspect the status of a field in terms of weed types and spatial crop and weed distribution. Our experiments suggest that our proposed system is able to perform a classification of sugar beets and different weed types in RGB images captured by a commercial low cost UAV system.

Farm Researchers Are Using Military Face-Recognition Software to Inspect Grapes


This little robo-farmer is just one project developed by FarmView, a multidisciplinary, multi-institution effort to put advanced technology to use on the farm. With an exploding global population, we need to increase food production by 70 percent over the next 40 years if we hope to feed everybody, according to the United Nation's Food and Agriculture Organization. The sorghum-stabbing robot project puts technology to use in the field of crop breeding. By using this vision system while driving through the fields, a farmer can easily get all that data and make more prudent water decisions.

Lettuce-Weeding Robots, Coming Soon to a Farm Near You


The Sunnyvale, California-based company makes farming machines. Blue River's machines are robots that help farmers manage their fields more efficiently. The jury is still out on whether this will be a fruitful sector for venture capitalists like those backing Blue River Technology, since large exits have been thin on the ground since Monsanto's 2013 acquisition of the Climate Corporation for more than $1 billion. Lawyer Roger Royse, whose California law firm specializes in representing agtech companies, tells Inc. that he thinks Blue River is a prime acquisition target, especially as the industry consolidates.

How Monsanto protects crops with artificial intelligence


The controversial corporation will use Atomwise's artificial intelligence expertise to discover molecules that could protect crops quicker. Atomwise uses deep learning algorithms to discover molecules that might have the desired effect, rather than look at every individual molecule. "Each growing season, farmers around the world are challenged with yield-robbing pests and diseases, yet the average crop protection product takes up to 11 years and more than $250 million to commercialize," said Jeremy Williams, Monsanto's agricultural productivity innovations lead. "Discovering new solutions is critical, and this collaboration will help bring much-needed crop protection solutions to farmers faster."

Monsanto looks into artificial intelligence technology with new research partnership


The process of developing and getting new crop protection technologies to market can stretch for more than a decade and require hundreds of millions of dollars. To home in on new ones in more timely and efficient ways, Monsanto is turning to artificial intelligence through a collaborative research agreement announced Wednesday. The biotech giant's partnership with Atomwise, a San Francisco-based company that uses artificial intelligence to accelerate the discovery and development of medicines, will look for crop science applications of the company's AtomNet technology, which a press release said uses "algorithms and supercomputers to analyze millions of molecules for potential crop protection products." "Instead of the traditional trial-and-error and process of elimination to analyze tens of thousands of molecules, the AtomNet technology aims to streamline the initial phase of discovery by analyzing how different molecules interact with one another," the release stated.