Impact of Artificial Intelligence in Agriculture

Impact of Artificial Intelligence in Agriculture
Impact of Artificial Intelligence in Agriculture| Source: Freepik.com

Introduction

Agriculture and farming is one of the most oldest and important practices and by passing time and increasing world population agriculture related issues also increasing. To counter these problems Agriculture Engineering and Technology interventions plays a major role. In the era of technological advancement IT, Mobile technology, robotics plays a vital role in agricultural growth. Now emerging technology like Artificial Intelligence is addressing agricultural issue like weather forecasting, Soil and crop health monitoring, detecting insects and pests, tackling labor challenge, providing market insights and supply chain management.

Importance of Artificial Intelligence in Agriculture:

Research and development of Artificial Intelligence in Agriculture today will decide the future of Artificial Intelligence in coming years. So, Research and development in Artificial Intelligence addressing some of the agricultural issues as follow:

AI in Weather Forecasting:

With changing climatic conditions, farmers find it difficult to determine the best time to sow seed. With the help of Artificial Intelligence, farmers can efficiently analyze weather condition. It also help them to plan the type of crop that can be grown and when seeds should be sown.

 AI in Soil and Crop Health Monitoring:

The type of soil and the nutrition of the soil influence the type of crop grown as well as the crop’s quality. Soil quality is deteriorating as a result of increased deforestation, and it is difficult to determine the quality of the soil but AI-based application can effectively detect nutrient deficiencies in soil, as well as plant pests and diseases, and provide farmers with recommendations on how to use fertilizer to improve harvest quality.

 AI in Detecting Insects and Pests:

Insects and pests are among the worst enemies of farmers, causing crop damage. AI systems compare satellite images to historical data using AI algorithms to determine whether or not an insect has landed, as well as what type of insect has landed, such as a locust or a grasshopper. Also, send alerts so that farmers can take the necessary precautions and pest control measures.

 AI in Providing Market Insights:

The AI provides market insights about agricultural produce that guide farmer’s decisions. For example, consumers searching for maize will be interpreted as increased demand for maize, and farmers can take this as a sign to sow maize despite of any other cereal or grain to reap profits.

AI in Agricultural Supply Chain Management:

AI based technology enables supply chain managers to make faster, more informed decisions by combining weather forecasts with their unique business insights. When farmers face supply chain challenges as a result of an emergency, pandemic, or disaster, access to near real-time location-specific weather views is critical. AI helps farmers make the best decisions about harvesting, processing, storing, and supplying their produce, as well as managing on-the-ground operations like logistics.

Examples of Artificial Intelligence in Agriculture:

Combining AI with other technologies like big data, robotics, drones, geographic information system (GIS), and many other technologies, most advanced AI enable tools can be built. Some examples of artificial intelligence in agriculture are as follows:

  • Harvesting huge volume of crops using AI enable robots.
  • Monitoring of soil and crop health using ML and AI enable apps.
  • Monitoring crop health using AI enable drones.
  • Effective weed management using AI enable sensors.
  • Providing advance level market insights using AI with big data.
  • Predicting more accurate weather conditions for suitable forming.

Disadvantages of Artificial Intelligence in Agriculture:

  • The process of adopting technology like artificial intelligence is very tedious and time consuming process.
  • Lack of technical knowhow in farmers will work as barrier of adopting Artificial Intelligence in Agriculture industries.
  • By increasing technologies threat of data privacy and security is also increasing as a result, artificial intelligence is no exception. Cyber-attacks and data leaks can put farmer’s data and the authentication of the AI technology they will be using in danger.

Conclusion:

Artificial intelligence in agriculture is not only assisting farmers in automating their farming, but to a large extent, AI solves the scarcity of resources to precise cultivation for higher and quality crop yield.  Increasing complexity of modern agriculture, AI is creating enormous opportunities in agriculture and allied industries. Improving machine learning or AI-based products or services like training data for agriculture, drones, and automated machine making will benefit AI in agriculture from technological advancement in the future, providing more useful applications to this sector and assisting the world in dealing with food production issues for the increasing population.

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