Logo :
Project owner's name :
Mrs Alrodini Nour
Mrs Alrodini Nour
Country of deployment for the project :
Jordan
Jordan
Sector :
Agriculture
Agriculture
What problem does your company want to solve? :
Current methods for testing or monitoring plant stresses and diseases involve sampling plant tissues and conducting laboratory tests. However, this process provides farmers with only one measurement
Current methods for testing or monitoring plant stresses and diseases involve sampling plant tissues and conducting laboratory tests. However, this process provides farmers with only one measurement
What solution does your company provide? :
"Early detection technology for external plant stresses using the Internet of Things and artificial intelligence, aimed at early prevention and continuous monitoring for farmers to identify plan
"Early detection technology for external plant stresses using the Internet of Things and artificial intelligence, aimed at early prevention and continuous monitoring for farmers to identify plan
Describe your project :
Current methods for testing or monitoring plant stresses and diseases involve sampling plant tissues and conducting laboratory tests. However, this process provides farmers with only one measurement, and there is a time gap between the time farmers take the sample and the time they receive the results, which can take several months.The delay in obtaining early prevention results for stress (whether biological, physiological, or insect-related) includes: 1. The spread of stress among plant tissues, exacerbating the problem and leading to tissue damage. 2. Farmers are forced to use large quantities of pesticides (chemicals) to address the stress. 3. Accumulation of these pesticides on the plant and crop, which are chemical compounds that negatively impact consumer health and the agricultural market, especially exports. An electronic device utilizing the Internet of Things and artificial intelligence for early detection of external stresses, pressures, or plant diseases such as physiological crop damage or insect pests. The device monitors these stresses by measuring the volatile organic compounds emitted by plants in times of danger, similar to sounding alarm signals in the form of volatile organic compounds. Through artificial intelligence, the data for each organic compound is analyzed to indicate the type of plant stress, and then sent to the mobile application.
Current methods for testing or monitoring plant stresses and diseases involve sampling plant tissues and conducting laboratory tests. However, this process provides farmers with only one measurement, and there is a time gap between the time farmers take the sample and the time they receive the results, which can take several months.The delay in obtaining early prevention results for stress (whether biological, physiological, or insect-related) includes: 1. The spread of stress among plant tissues, exacerbating the problem and leading to tissue damage. 2. Farmers are forced to use large quantities of pesticides (chemicals) to address the stress. 3. Accumulation of these pesticides on the plant and crop, which are chemical compounds that negatively impact consumer health and the agricultural market, especially exports. An electronic device utilizing the Internet of Things and artificial intelligence for early detection of external stresses, pressures, or plant diseases such as physiological crop damage or insect pests. The device monitors these stresses by measuring the volatile organic compounds emitted by plants in times of danger, similar to sounding alarm signals in the form of volatile organic compounds. Through artificial intelligence, the data for each organic compound is analyzed to indicate the type of plant stress, and then sent to the mobile application.