Engineering news
Aerospace engineers from the UK are partnering with Chinese universities to improve the agriculture industry in China as part of a £1 million project.
The project aims to develop unmanned autonomous ground and air vehicles so they can remotely collect observation data about crops in a timely and repetitive manner across a wide area. This information will then be used to evaluate soil and crop health and improve crop yields.
The project, which is called “Enabling wide area persistent remote sensing for agriculture applications”, also aims to ensure the enabling technologies can be operate without expertise.
Professor Wen-Hua-Chen from the department of aeronautical and automotive engineering at Loughborough University, said that the increasing and ageing population, demand for energy and fresh water and more extreme weather events would pose “serious challenges” to agriculture in the coming years.
“Remote data collection to evaluate soil and crop health has an important role to play in developing sustainable agriculture for rapidly developing countries like China.
“This data can be utilised for the early detection of diseases and pests, but there is still work to be done in ensuring unmanned ground and air vehicles can cover vast areas to return more data without hefty operation costs and reliance upon the operator’s experience and skills.
“It is our intention that this project will improve strategic and tactical decision making by developing computer algorithms to improve overall farm management. Targeted interventions and site specific treatments will be made possible thanks to better data collection and analysis.”
The project involves Cranfield University, the University of Manchester and the National Institute of Agricultural Botany, as well as the Beijing Aerospace Automatic Control Institute and Beihang University.
It is believed that precision agriculture, also known as “smart farming”, will increase the quality and quantity of agricultural production by using sensing technology to make farms more connected. Examples include the measure of soil moisture and nutrition using airborne sensors on unmanned aircraft, automatic detection of weeds with airborne cameras, and co-ordination with autonomous mechanical weeders for treatment.