Search results
Results From The WOW.Com Content Network
An agricultural drone is an unmanned aerial vehicle used in agriculture operations, mostly in yield optimization and in monitoring crop growth and crop production. Agricultural drones provide information on crop growth stages, crop health, and soil variations. Multispectral sensors are used on agricultural drones to image electromagnetic ...
ZenaTech’s DaaS business model allows governments, builders and developers, farmers, oil and gas companies, environmental firms, etc. to utilize a complete drone solution for a specific application─ i.e., land surveying, crop management, inspection, safety, or compliance application – and purchase it on a pay-as-you-go basis rather than ...
An agricultural robot is a robot deployed for agricultural purposes. The main area of application of robots in agriculture today is at the harvesting stage. Emerging applications of robots or drones in agriculture include weed control, [1] [2] [3] cloud seeding, [4] planting seeds, harvesting, environmental monitoring and soil analysis.
Today, this often involves agricultural drones, which are paired with NDVI to compare data and recognize crop health issues. One example of this is agriculture drones from PrecisionHawk and Sentera, which allow agriculturalists to capture and process NDVI data within one day, a change from the traditional NDVI uses and their long lag times. [19]
Valeria Kogan is the CEO of Fermata, a software-development company specializing in agriculture. Her team develops AI tools to reduce crop loss that causes food waste and greenhouse gas emissions.
Precision agriculture (PA) is a management strategy that gathers, processes and analyzes temporal, spatial and individual plant and animal data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of ...
Satellite crop monitoring technology allows to perform online crop monitoring on different fields, located in different areas, regions, even countries and on different continents. The technology's advantage is a high automation level of sown area condition and its interpretation in an interactive map which can be read by different groups of users.
Computer vision is used to monitor crop health, detecting diseases and nutrient deficiencies early. For example, drones equipped with multispectral cameras can capture images of crops, which are then analyzed using machine learning algorithms to identify health issues. Machine learning algorithms can analyze data from sensors and drones to ...