Sat, 07/10/2021 – 19:24
AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decision-making. AI techniques are widely used to solve a variety of problems and to optimize the production and operation processes in the fields of agriculture, food, and bio-system engineering.
Agriculture plays a significant role in the economic sector. AI in agriculture is the main concern and an emerging subject across the world. The population is increasing tremendously and with this increase, the demand for food and employment is also increasing. The traditional methods which were used by the farmers were not sufficient enough to fulfill these requirements. Thus, new automated methods were introduced. These new methods satisfied the food requirements and also provided employment opportunities to billions of people.
The technologies which are AI-based help to improve efficiency in all the fields and also manage the challenges faced by various industries including the various fields in the agricultural sector like the crop yield, irrigation, soil content sensing, crop- monitoring, weeding, crop establishment.
The agricultural industry faces various challenges such as a lack of effective irrigation systems, weeds, issues with plant monitoring due to crop height, and extreme weather conditions. But the performance can be increased with the aid of technology and thus these problems can be solved. It can be improved with different AI-driven techniques like remote sensors for soil moisture content detection and automated irrigation with the help of GPS.
The various ways in which AI has contributed to the agricultural sector are as follows:
- Image recognition and perception: drones or UAVs are becoming increasingly popular to reach great heights and distances and carrying out several applications.
- Skills and workforce: artificial intelligence makes it possible for farmers to assemble a large amount of data from the government as well as public websites, analyze all of it and provide farmers with solutions to many ambiguous issues as well as it provides us with a smarter way of irrigation which results in higher yield to the farmers.
- Maximize the output: Now we can meet the market trends, yearly outcomes, consumer needs, thus farmers are efficiently able to maximize the return on crops.
- Chatbots for farmers: Artificial intelligence-powered chatbots, along with machine learning techniques have enabled us to understand natural language and interact with users in an away more personalized way.
The fate of cultivating depends to a great extent on the reception of various cognitive solutions. While large-scale research is still in progress and some applications are already available in the market, the industry is still high. When it comes to handling realistic challenges faced by farmers and using autonomous decision-making and predictive solutions to solve them, farming is still at a nascent stage. To explore the enormous scope of AI in agriculture, applications need to be more robust. Only then will it be able to handle frequent changes in external conditions, facilitate real-time decision making and make use of appropriate framework/platform for efficiently collecting contextual data.