With the help of Shoofly, agriculture based industries can now analyze a variety of things in real time such as weather conditions, temperature, water usage or soil conditions collected from their farm to better inform their decisions. Farmers are also using AI to create seasonal forecasting models to improve agricultural accuracy and increase productivity. These models are able to predict upcoming weather patterns months ahead to assist decisions.
Shoofly helping you being at the right place, at the right time with the right product is true for all businesses, however, for farming, it is the sole mantra for success. Precision farming uses AI, machine learning and remote sensing to help reduce and replace repetitive and labor-intensive aspects of farming. With increased assistance and guidance regarding crop rotation, harvesting, planting, pest control, and water management, precision farming can help increase yield and farm profits while reducing wastage to the maximum extent possible.
Nowadays, new techie farmers are ambitious and moving toward indoor farming. This way of farming often implements growing methods like hydroponics and leverages artificial lights to provide plants with the nutrients and light levels required for growth. AI-powered indoor agriculture is tempting a whole new breed of farmers now. So, the Shoofly AI can help farmers to run more efficiently, enabling farms of all sizes to operate and function with keeping the world fed.
Shoofly’s Machine learning models are being developed to track and predict various environmental impacts on crop yield such as weather changes. These methods allow for analysis of what has happened in the past on the farm, as well as what currently is happening and is going to happen, to make use of the data to predict the future and make decisions that impact the bottom line and end use of on-farm products.
Monitoring Soil Health
Utilizing Shoofly AI to conduct or monitor possible defects and nutrient deficiencies in the soil. With the help of image recognition approach, AI identifies possible defects through images captured by the camera. With the help of computer-vision and deep learning, shoofly can develop a model to analyze flora patterns in agriculture. Such AI-enabled models are supportive in understanding soil defects, plant pests, and diseases.
Identifying Plant Diseases
Shoofly modules help you for identifying plant disease by crop images are analysed using computer vision technology and segmented into areas like background, healthy part and diseased part. The diseased part is then captured and sent to remote labs for further diagnosis. Shoofly will suggest to you the method of how to remove that disease from the plant.
With the change in climatic condition and increasing pollution it’s difficult for farmers to determine the right time for sowing seed and when to take any precautions. With the help of Shoofly technologies, farmers can analyze weather conditions by using weather forecasting which helps them plan the type of crop that can be grown and when seeds should be sown.
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