Advancements in Precision Agricultural Insights
In five to 10 years we will see more aerial and ground robots operating alongside the farmers. And farmers will be able to proactively manage their farms using modern AI capabilities and generate better yields and profits-with optimum sustainability.
Food Production Steps Up to Meet Global Demand
Using a model that blends aspects of technology, agriculture and science, Living Greens Farms is setting a template for the future of farming. With the addition of a new grow room in 2019, Living Greens Farm raised the total space of its aeroponic farm to 60,000 square feet.
Smart Solutions Help Farmers Combat Climate Change
As farmers learn to adapt to a changing climate, the industry must also reduce its own carbon intensity by 2030 in alignment with the Paris Agreement to reduce greenhouse gas emissions.
How Vertical Farming will shape the Post Pandemic Food Supply Chain
We're building for a future where modular vertical farming solutions are an accessible means of food production in urban areas. By modular vertical farming solution, we are referring to turnkey grow systems from the size of a shipping container down to a household appliance.
Readers Choice 2020: Satellite Imaging for Agriculture
About 12% of the Earth's land is used for growing crops. As the world's population grows, greater demands are placed on agriculture than ever before, and growers are depending on satellite data to increase their crops.
Readers Choice 2020: 5G Is Coming to Agriculture
5G speeds surpass wireline network speeds and offer latency of 1 millisecond or lower, which is advantageous for applications that require real-time feedback. 5G will facilitate an increase in the amount of data transmitted over wireless systems.
So, You Want to be a Farmer
But, if you are set on becoming a farmer, there are many schools to attend and courses that you can take. There is no degree necessary to start plowing, but it would be beneficial to have a knowledge of the industry.
Challenges of Developing a Safety System for an Agricultural Site
Each industry has additional standards that must be followed. For example, earth moving equipment used in mining has additional standards than a harvester in an agricultural setting.
Cultivating Farmland Precisely and as Needed
Digitized and automated processes are becoming increasingly important in modern agricultural enterprises. Machine vision methods play a key role here. Among other things, they can be used for a variety of precision farming applications.
Smart Technology in Farming
Smart farming involves the incorporation of advanced technologies into existing farming methods in order to increase production efficiency and the quality of the agricultural products.
Traceability in the Food and Beverage Supply Chain
Manufacturing is beset by major challenges that are made worse by hyper shifts in supply and demand. Three main areas that are persistently an issue for Manufacturers are quality and safety issues, waste and underperforming assets, and high environmental impact.
Synthetic Biology in Agriculture
There are ways to improve the carbon efficiency of plants, while increasing production. By making use of diversified cropping systems growers can reduce the carbon footprint up to 300 %.
Farm Science Review 2020
For the first time, the Ohio State University's Farm Science Review, scheduled for September 22 to 24, will be a virtual show. The farm show, sponsored by Ohio State's College of Food, Agricultural and Environmental Sciences would normally have over 100,000 attendees.
Implementing AI Data for Pest Management
You can place our sensors in your field when the insects arrive, the sensors can figure out what type of insect it is. If it is a beneficial or neutral insect, it does nothing. However, if it is a bad bug aka pest, it sends the information to the cloud.
Case Study - Asparagus Picking Agricobot
ST Robotics has been making and selling low cost bench top robots for 3 decades. Along the way we have been involved in a wide range of applications and projects. One major application area is agriculture.
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Artificial intelligence can be used, for example, to classify fruit varieties or to identify damaged parts (e.g. apples with marks or colour deviations). To cover all possible variances with classical image processing would be very time-consuming and costly. AI is able to solve these challenges in no time at all. With IDS NXT ocean, there is now a user-friendly complete solution for industrial applications available. It requires neither special knowledge in deep learning nor camera programming.
