How can AI transform Agriculture?

As a matter of fact, Usage of Artificial Technology in Agriculture plays an important role but Currently, world is facing the severe challenge of population growth. The world population at that particular time is approximately to 7.7 billion. Scientist have predicted that the population will increase to 10 billion in 2050. Today totally 820 people on the worldwide are hungry out of the 7.7 billion.

Drastic reality

Though This is very drastic reality, and if we do not take steps currently, then our coming generation will suffer from it sure. The statics demands from the high leadership of the agriculture industry to take necessary steps to provide the solutions of the growth in the food production.So, There are lot of research have been currently done on improving the agriculture industry and this process will be going so on.

Artificial intelligence algorithms:

As, it is the fourth industrialist revolution, everything going towards the automation using the artificial intelligence algorithms and techniques. Like the other fields of life, agriculture industry has also the areas which can be improve by using the artificial intelligence. In most of the agriculture countries, most of the farmers are the aged.

Economic Benefits:

There are few people young people who move towards this fields. So, the old aged farmer finding difficulty to finding different problems and their solution, like whether the weather is suitable to cultivate the specific crop, crop is effected due to some disease, weather prediction, cultivated crop growth etc. So, if we manage these things automatically, then it has the directly impact on the production of the cultivated crops as well as the economic benefits of the farmer.

Computer vision:

Artificial intelligence in Agriculture fields like computer vision will be helpful to solve these problems. Computer vision along with the deep learning and machine learning algorithms can be applied to build those applications which can help the agriculture industry of the specific county. There are several applications which have built using the machine learning and deep learning techniques like weather forecast, crop disease detection, crop growth monitoring etc.

Use of AI in agriculture?

There are multiple usages of the artificial intelligence in the agriculture industry. Currently, artificial intelligence helped the agriculture field into the three major categories. Which are described as follows:

Agricultural Robots:

Artificial intelligence industry is working on the development of the autonomous robots, which can perform the agriculture related tasks automatically. These tasks involve the harvesting of the crops in the large scale most effectively and accurately. Moreover, it can perform the task in a huge amount with the faster speed as compared to the human as shown in figure 1.

Artificial-intelligence-industry-is-working-on-the-development-of-the-autonomous-robots
Figure 1 : Agricultural Robots

Soil and Crop Monitoring:

Automatically monitoring of the soil and crop can help the agriculture industry in many ways like to improve the health of the cultivated crop, safety from the diseases and the insects etc. as depicted in figure 2. Many companies taking the leverages from the computer vision and deep learning techniques to monitor the health of the crop and the soil to increase the productivity of the crops.

Automatically-monitoring-of-the-soil-and-crop

Predictive Analysis:

Machine learning along with the deep learning is quite beneficial for the prediction of the different environmental factors, which directly affect the crop health and productivity. Like, machine learning algorithms will be helpful for the weather predictions, like weather is suitable for the cultivating the specific crop etc.

There are several applications exists which assists the farmers by generating the alerts relating to the weather. These types of applications will quite helpful, because based on the generated alerts the farmers taking the necessary steps to overcome difficult situation regarding to crops.

Weed Control:

One of the major challenge which agriculture industry being currently faced is how to control the weed. Herbicides resistance is one of the top priority of the farmers and the current artificial intelligence industry. Such kind of robotic machine have been shown in the figure 3.  Companies are developing different solutions that are beneficial for the farmers to actively handle the weeds against their crops.

technology-for-Weed-Control
Figure 3 : Weed Control Device

Techniques and Technology

There are lot of techniques and tools which used for the development of the autonomous robots and machines which helped the agricultural industry. Most of the agriculture related task done with the help of the computer vision techniques, because major tasks of predictions in agriculture field associated with the vision.

Moreover, data science and sound analysis will also be helpful for the generating the agriculture friendly applications. Data science techniques used to generate predictions based on learning of the previous weather conditions and then forecast it for particular day.

Sound analysis:

Similarly, sound analysis will helpful to identify sound of the animal or insects which will be harmful for the crops. The recognition of the suspicious sounds will identify the respective person to take the necessary steps to handle the situation.  Most of the above discussed applications built with the help of the deep learning techniques and algorithms.

Development of algorithms:

These algorithms developed using the different open source tools and technologies like tensor-flow, pytorch, caffe etc. Although, we achieved the state of the art accuracy using deep learning algorithms. But to train the deep learning model, large amount of dataset and huge computation power is a big challenge.

Future Work and Discussions

From the recent few years, artificial intelligence and machine learning have found intensively on the farming fields and agriculture products. According to the statistics, market share of AI in agricultural industry is USD 600 million in 2018. In which expected to reach the USD 2.6 billion at the end of the 2025.

Factors:

There are some factors which increase the demands of AI in agricultural industry:

  1. The increasing amount of the population worldwide demands the more production from the agriculture industry.
  2. The demand of the effective and accurate automatic system, to increase the productivity of the crops.
  3. Worldwide government of the different countries supports the adaptation of the latest and fully automatic agricultural techniques.
  4. Through AI based algorithms and techniques, we can achieve the better agricultural outputs in less time with huge volume.

You may also know The use of Internet of Things in Artificial Intelligence

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