Novel Applications Of Optical Sensors And Machine Learning In Agricultural Monitoring 2nd Jibo Yue by Jibo Yue, Chengquan Zhou, Haikuan Feng, Yanjun Yang And Ning Zhang 9783036597997, 3036597999 instant download after payment.

Agricultural production management is facing a new era of intelligence and automation. With developments in sensor technologies, the temporal, spectral, and spatial resolution from ground/air/space platforms have been notably improved. Optical sensors play an essential role in agriculture production management. Especially, monitoring plant health, growth condition, and insect infestation have traditionally been approached by performing extensive fieldwork.
The processing and analysis of huge amounts of data from different sensors still face many challenges. Machine learning can derive and process agricultural information from the optical sensors onboard ground, air, and space platforms. Advances in optical images and machine learning have attracted widespread attention, but we call for more highly flexible solutions for various agriculture study applications.
We believe that sensors, artificial intelligence, and machine learning are not simply scientific experiments, but opportunities to make our agricultural production management more efficient and cost-effective, further contributing to the healthy development of natural-human systems.