Artificial intelligence holds the agreement of driving an agricultural revolution right at a time when the world requires producing more food using fewer resources.
Future holds a robotic lens that analyses a tomato seed in greenhouses, and an artificial intelligence algorithm predicts exactly how much time it needs before picking, packing, and consuming it by the customer at the grocery store.
Applications of AI in agriculture
Optimizing greenhouse environments with micro sensors
Active environmental management demands constant monitoring via cameras and micro sensors that stores the data in central data storage where Fuzzy Logic Controllers (FLCs) and Artificial Neural Networks (ANNs) algorithms perform the real action in the back. Microsensor predictions reduce the guesswork and assist growers to generate an environment with better quality yield.
AI algorithms built-in tools predict pest infestation, weather patterns, or soil damages to refine planning and farm management. Predictive analysis tools help growers to make informed decisions.
Growers with Wi-Fi access utilize AI applications to get a consistently customized strategy for their lands. With this growers encounter raised food demands in production and profits without compromising any of the natural resources.
Leverage Smartphone-based AI, IoT applications
Smartphone-based solutions notify and alerts growers to reduce the probable outbreaks of pests and diseases, thus minimizing yield losses. Similar to this Sperotec’s CanopyMesh IoT Platform helps to integrate location-based services, lighting management, environmental control together remotely with quality interfaces that profit growers for many seasons to come.
Agriculture Robots (Agbots)
Opportunities for agricultural robots are vast, including but not limited to fruit picking autonomously, spraying weed control, helping growers to minimize the environmental impacts, and enhance efficiency.
Agbots can safeguard human workers from the harmful effects of handling dangerous chemicals through the methods of spraying and can lessen the use of pesticides.
Drone applications are utilized for high-quality imaging and better crop monitoring processes. This advanced technology scans analyses and collects data in real-time without interrupting any current procedures while helping growers to identify crop progress methods. Drones attached with smartphones give growers leverage to manage them remotely with more precision accuracy, therefore disclosing data about soil colour, diseased plants, leaves shape. This assists growers to identify disorders and suggests more desirable cures to protect the crop.
Analysing soil nutrients
With help of infrared rays, sensors, and cameras, AI aids growers to scan soil for its nutritional variables which help growers understanding the response of particular seeds with various seeds, how weather impacts the soil and possibilities of pests and diseases.
Some examples of farming in greenhouse activities include, weed control, nutrients data, harvesting and packaging, lettuce thinning, diagnosing pests and soil defects, soil analysis, crop health monitoring, weather, pests and disease prediction. It is noticeable that to grow in the farming industry, AI tools are necessary for easy utilization.
Benefits of AI in agriculture
- An effective way to harvest, produce, and sell crops.
- The accurate speed with fewer errors.
- Accessible demand and supply of the market make planning and storing effortless.
- Computer vision technology assists growers to analyse yield and soil conditions, leading future generations with promising insights.
- Robots and AI minimizes the use of pesticides by up to 80%.
- They can be small in size, allowing to accumulate near-crop data and execute mechanical weeding, spraying, mowing, and fertilizing processes.
- The robots decrease the cost of production and deliver products of premium quality.
- Delivers high-quality products and lowers the cost of production.
- The development in Artificial Intelligence technology has established agro-based businesses to grow more proficiently.
Investing in the smart field explains the greater possibility of better productivity and balancing quality food essentials. AI is re-evaluating the conventional design of agriculture. AI has produced automation in agriculture that assists growers to successfully monitor crops remotely without any location barriers.
The execution of IoT, big data, and AI in agriculture have intense effects on small-scale agriculture businesses which will continue to be more profound in years to come.