The Growth of Vision Systems in Agriculture

Agriculture IndustryVision Systems Bring Agriculture into a Smarter, Automated Future

Vision systems and software are transforming traditional agricultural practices, resulting in highly measurable, automated, and reliable forms of raising livestock and plants. In recent years, vision technology has emerged in a wider variety of agricultural applications, proving its capabilities for enhanced productivity, stricter quality control, and advanced farming practices.

Smart Agriculture Market to be Worth $13.50 Billion by 2023

In fact, it’s estimated the entire smart agricultural market will be worth $13.50 billion by 2023, growing at a 12.39% compound annual growth rate (CAGR)1. This rapid growth is primarily driven by a need to remain globally competitive by being more productive, additional government support and legislation for more eco-friendly agricultural practices, and an increasing demand for food delivery to a rapidly growing human population.

Vision technology has made its way into this expanding industry in a number of ways. Most prominently, advanced vision systems, both multi-spectral and in the visible spectrum of light, are used in drones for soil and field analysis, crop monitoring, irrigation analysis, and for developing normalized difference vegetation indexes (NVDI) to identify unhealthy crops.

More recently, 3D embedded vision systems are being used to help autonomous mobile robots (AMRs) identify and harvest fruits and vegetables in modern greenhouses. Inspection systems are also used to grade, measure, and sort products after they’ve been picked or processed but before they’re shipped down the food supply chain. Even more advanced vision systems can be used for high throughput plant phenotyping (HTPP), where more desirable phenotypic traits can be identified and used for breeding to produce more resistant and aesthetically pleasing plants.

Artificial intelligence (AI) will also play an important role in the future of vision systems in agriculture. For example, to prevent injury or infection within a raised pig population, a vision system for monitoring pigs could alert a farmer before a bout of harmful tail biting breaks out. Other AI-enabled vision systems can be used in future greenhouses to control exactly the nutrients a fruit or vegetable receives and indicate the precise moment it should be picked.

Vision systems in agriculture are being used in a diverse range of applications. As the technology advances and demands on farmers to produce food at higher levels of productivity increase, vision systems will be incorporated in ever more ways.