Computer vision in agriculture: What’s it and what it can do?

A brief look over the human history will depict one clear thing that each civilization of mankind is slightly different from its predecessor and each of them is a better, more advanced form than the previous one. George Bernard Shaw has written that the very progress in human life is dependent on change in mind set and without this change in approach advancement is not possible. This is applicable to every walk of life including the field of food and agriculture, that has greatly evolved over the course of last 10,000 years.

Great historical civilization like the Achaemenian, Babylonian, Egyptian, Roman and all the way to the modern civilization all are uniquely different in their ability to grow food and crops. The world history is full of famine events, such as it was in case of Prophet Yusuf (Joseph) where the most advanced civilization of the time was tested with seven fat years and seven lean years. Failure to manage such crisis has often resulted in demise and ultimately dismantlement of empires, such as it was in case of ancient Rome during the 5th century BC. History clearly tells us that many of these historic civilizations failed to adopt the changing dynamics and it has resulted in to complete eradication of such societies.

by Faizan Ali.

Over the course of last 3 centuries global population has rapidly increased from 1 billion to 8 billion and all this has mainly been possible due to production of food and resources to feed the world. The green revolution of 1970’s has great significance in this regard which ensured massive food productions, that allowed the world to think less about sustenance and more about making new technologically gains. This new approach (of green revolution) allowed our civilization to move further ahead, but it is now beginning to see its limitations. The green revolution revolved around usage of various natural resources with focus on production without much consideration of efficiency. Now as the world enters in new era where the globe population is projected to touch 10 billion mark, along with major climate change issues and resource constraints, the very existence of modern civilization is dependent on our ability to change our approach of growing food in a more productive and efficient manner.

All this can be made possible with an element of reverse engineering, where the world will now use more of modern technology to grow food in effective way for survival instead of growing food to much food with inefficient way so that the world can focus on discovering new Tech (as in case of 70’s green revolution). Among the major discoveries of the past century one that has made the greatest impact of all are the digital innovations

that had altered the very reality in which we live, from email, IOT to the modern Artificial intelligence approaches. These technologies are now transforming everything including the field of agriculture, this includes climate related risk assessment and modelling, pest and disease detection as well as smart tracking of pest and livestock. Amon these modern technologies one of the most prominent one is computer vision (CV), which allows machines and robots to access, presume, perceive and understand the visual world in a similar manner to humans. A basic application of this technology includes a combination of cameras, IOT sensors and high performance computers to enable non-contact sensing and surveillance of agriculture field at massive scales. CV technology has received praise over recent years for enabling real time detection and trouble shooting of challenges faced by growers. This empowers the grower to be robust in his growing tactics in a much more efficient and cost effective manner. Recent advances in deep learning algorithms has revolutionized CV filed and further enhanced the possibilities for more broader application of technology, as well as more effective real time remote diagnosis of issues with effective video analytics.

At present CV technology has various technical, research and field applications, with prospective growth in applications and effectiveness of the tech. One of the primary implementations involves advance drone technologies mounted with cameras for monitoring of soil, crops, as well as estimation, detection of abnormalities in precision agriculture. Drone based CV applications enable large area sensing and surveillance, providing a substitute for labor shortage with 24/7 monitoring of field conditions. Also, this recent advancement has enabled detection of crop based on their expected ripeness and perishability status. In addition to this research based applications like the high throughput phenotyping (HTP) is empowering researchers across the globe with the ability to unravel many genetic and physiological mysteries of plant crops. CV applications in HTP enables better analysis of numerous plant characteristics including; their growth patterns, which type of climate is best suitable for them as well as the genetic makeup of growing plants.

These nascent technologies offer many benefits for the sector; it can assist in minimizing overall crop failure risk due to sudden climate anomaly, precision agriculture, early disease detection and warning system for effective disease management. AI and computer vision technologies are expected to become a multi-billion dollar industry with in this decade with far reaching significance and value addition to the sector. Furthermore, global institutes like the Wageningen, Cornell, UC Davis, China agriculture and University Florida are working relentlessly to further advance in these fields in order to ensure global food security in face of unprecedented challenges.