AI In Agriculture

Agriculture

Artificial intelligence for agriculture is revamping traditional farming, which is the wholesale occupation for many across the world. Also, with rising demand, farmers need to ensure that their products can fulfil it. At Anubrain, we provide end-to-end solutions and services to the farming community and foster AI in agriculture. We use real-time data and AI to power our technology to solve real challenges at the farm level and throughout the food chain. Our team is capable of developing Precision Agriculture (PA) technologies, especially AI-enabled remote-sensing technologies. PA is a technique of farm management that employs information and communication technology to optimize farming.

Problems we are solving

Crop Classification

Remote sensing is one of the evolutionary technologies and it has various applications with AI in agriculture. Whether it’s visible, thermal or microwave domain, every spectrum administers decisive information.

Crop Classification is often done by either conventional methods or by automatic machine learning (ML) based methods. Crops are categorised using communication system points (GCPs’) by employing unsupervised learning by identifying specific spatiotemporal crop signatures.

Crop Yield Forecasting

Climate and its unpredictability are one of the major factors behind the reduced rate of crop production. Meteorology is thus essential for improved crop management, good crop yield, and reduced wastage of produce.

Agriculture has several other related industries like the sugar industry that depend on the yield of sugarcane. If the yield is affected, the related industries also suffer. So, crop yield forecasting using AI and machine learning for agriculture comes into the picture. It helps them take important decisions and plan for the future in advance.

Crops demand forecasting

Most of the time, farmers or agro businessmen suffer financially due to crop loss. The most important cause for this is inappropriate crop selection or sometimes needing to get a justified price for the crop due to surplus production of the crop in that season.

Thus, Artificial Intelligence (AI) for agriculture is used for forecasting. By analysing the soil and environmental factors in a particular region, the best crop for farming is predicted.

This prediction will help the farmers to choose appropriate crops for their land according to the soil type, temperature, humidity, water level, soil fertility, etc. and indirectly, help in increasing the crop yield

We Think Critically & Develop Creatively

Fertilizer
Management

AI for agriculture is used to identify and overcome the problems associated with the use of fertilizers. One way to measure the accurate amount of fertilizer required by the crop is image processing.

Soil Quality
Assessment

Today, different Al techniques and advanced sensors mounted on UAVs conduct soil quality assessment. The AI-powered devices collect and analyze multispectral and hyperspectral images to examine soil quality.

Water Management
Technology

Using loT and RS techniques, the use of irrigation water in the agricultural field can be addressed efficiently. The adoption of AI water management technology enhances water use efficiency in irrigation, increases overall crop yield, and improves product quality.

Land Use
Planning & Management

AI in agriculture utilizes techniques such as Geographic Information Systems (GIS) and Remote Sensing (RS) for land planning and management. Therefore, farmers can get more ideas to utilize their land for agriculture and related businesses.

Our Services

We Strive To Make Al Work For You

AnuBrain specializes in delivering end-to-end data-driven application development with cutting- edge technologies such as machine learning, deep learning, computer vision, natural language processing, IoT, and blockchain. Our team can assist you with various business needs and give you peace of mind even when you entrust us with your most critical ones.