Is Artificial Intelligence the Future of Agriculture? Amazing Applications and Forceful Impact.

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ARTIFICIAL INTELLIGENCE IN AGRICULTURE

Is Artificial Intelligence the Future of Agriculture? Amazing Applications and Forceful Impact.

The Need for Artificial Intelligence in Agriculture

1.  The population of the world is increasing at a fast pace. This led to a surge in the demand for food and employment. The world population is likely to reach nine billion in the next 30 years. This population requires a boost in agricultural production by 70% to meet the rise in demand. With the increase in population, land, water and other resources are becoming scarce. There is a need for an intelligent approach to farming, to make it efficient and more productive. The conventional methods used by farmers are not enough to meet the growing demands. The introduction of innovative methods in agriculture is the need of the day. Problems of population expansion, climate change, and food safety are paramount. They have forced farmers towards innovative ways to protect and improve crop yield.

2.  Artificial Intelligence in agriculture can provide answers to the above problem. Artificial Intelligence is marking its presence in all industries. Every business is working towards automating certain work by using intelligent machinery. Artificial Intelligence is a growing trend in the Agricultural industry. This technology is still in its nascent stages, especially in India. There is a wide scope for AI in this field. The Role and applications of Artificial intelligence in agriculture are immense. It includes irrigation techniques, weed control, climate prediction, water management, soil management. It also includes the use of robotics for manual works. AI is progressing as the Agricultural industry’s technological advancement.

Application of Artificial Intelligence in Agriculture

3.    AI can add a lot of value to the agriculture system. It will expand the food producer’s ingress to many arenas. It includes access to the marketplace, information, counseling, and the latest trends. Prompt and correct information develops a healthy demand-led supply chain. Sensors, satellite images, IoT devices, and drones can collect agricultural data. AI can corroborate this data with weather data, soil health data, and market prices. This in turn will support predictive farming. This information will further enhance the assessment of seeds, fertilizers, and pesticides. This information is decisive both during pre-harvest and post-harvest.

4.       We can divide the application of AI in agriculture into three categories: –

(a)          Agricultural Robotic

(b)          Crop and Soil Monitoring

(c)          Predictive Analysis

Agricultural Robotics

5.         Robots are being developed to carry out agricultural tasks that need manual labour. These robots can do tasks like weeding and harvesting much than humans. They can identify weeds and can also detect the quality of the crops. Machine vision enables the robots to observe and identify the plants. take appropriate action on each plant.

(a)  Weed Control.  The uncontrolled spray of herbicide on crops, end up spraying the same on weeds as well. This leads to herbicide resistance in weeds over a while. Robots with camera vision pass live pictures to the control centre.  This assist in the precise spraying of herbicides on the plants and not on the weeds. This precise technique of robots stops the herbicide resistance of weeds. It reduces the usage of chemicals and increases crop productivity. It also reduces damage caused by herbicides.

(b)  Crop Harvesting. Crop harvesting is one of the most labour intensive and time-consuming work. Autonomous machines and robot can navigate and take plant-specific action. Autonomous and self-driven tractor and machines have enormous labour saving capabilities. They can cut, collect and even stack and pack crops.

(c)  Seed Planting and Aerial Imagery.   Remote-controlled drones are capable of spreading seeds in the farmlands. These drones are also useful in keeping a close observation of crops in big farm areas. Monitoring vegetation’s has become effortless.

Crop and Soil Monitoring.

6.         AI can track and identify defects in crops and also detect nutrient deficiency in the soil. Drones and satellites capture images of the soil and crops. These images are then processed to identify the defects.

(a)  Soil Monitoring.     Drones and satellites capture the images of the crops and soil of the farmlands. Image processing and comparing with the existing database is then carried out. This process gives out the assessment of crop and soil health conditions. It can detect nutrient deficiencies in the soil. It assesses fertilizer and other nutrients for improving soil health. That in turn improves the quality of the harvest.

(b)  Crop Monitoring.  Satellites and drones capture images of the farmland. AI-enabled computer systems and experts in this field compare and analyse these images. This assessment brings out a detailed analysis of the health of the existing crop. Farmer uses this assessment to identify the problems. Farmer than applies suitable methods to prevent crops from pests and other diseases.

7.         Predictive Analysis.   With the help of satellites, AI can predict environmental changes. It also brings out the effect it will have on the crops. AI assesses information about climatic conditions well in advance. The farmer uses this information to plan his complete cultivation cycle. It can predict the climatic impact on crop yield with the change of weather conditions. AI provides information about suitable crops for the season. It even informs about the ideal planting period and correct place for farming.

Advantages/Disadvantages of AI in Agriculture. (Pros and Cons of AI in Agriculture)

8.         Advantages of AI in agriculture. There are many advantages of AI in this field. The main advantages of AI in Agriculture are as follows:-

(a)          Identification and Detection of Pests and weeds.  AI-enabled cameras and sensors help detecting weeds, spotting pests, insects. They can also detect diseases in the crops. They are much efficient than the manual labour for the said task.

(b)          Speed and Efficiency.  AI machines function at a much faster pace and make lesser mistakes and than any other means.

(c)          Economy.  It uses precision spraying which in turn reduces the use of pesticides by up to 80%.

(d)          Cost Effective.  There is a big initial investment in AI. In long run, AI turns out to be much more cost-effective.

(e)          Relentless.  Robots and AI machines do not have human problems and emotions. They do not get unwell or get weary and do not need rest or leave.

(f)           Reduce manual labour.  Robots can reduce manual labour.

(g)          Less cost of crops.  It can produce crops with a much lesser cost of production

(h)          Future Planning.  It can help the farmers plan the crop cycle based on the likely weather conditions.

(i)           AI-enabled automatic self-control machines perform almost all tasks on the field. They are efficient than humans in performing most of these tasks. This saves on manual labour and also money.

(j)           Small machines perform mechanical weeding, fertilizing, spraying, and mowing. They are even used for cutting, stacking and packing crops.

9          Disadvantages of AI in Agriculture.  AI has many benefits but also have many inherent problems too. These problems create some apprehensions about its implementations. The main disadvantages of AI in Agriculture are: –

(a)          Very expensive.  It is very expensive and beyond the reach of most the farmers

(b)          Heavy maintenance.  It requires constant and regular maintenance

(c)          Unemployment.  With all manual work taken over by machines, will generate unemployment.

(d)          Research.  There is an extra cost of continuous research and development in this field.

(e)          Limited Development.  The technology is still in its nascent stages. Most of the robots or drones at present have very limited capabilities. These limitations make them a little impractical to be effective on the field.

(f)           Limited Reach.  The technology is much beyond the reach of most countries.

(g)          Lack of know-how.  Most of the developing countries don’t have trained farmers to use this technology.

(h)          Negative impact on the environment.  Environmentalist worry about the ways it can disturb the ecology.

(i)           Costly errors.  The errors created by AI machines are much more destructive than human errors.

(j)           It cannot replace humans.  AI technology is still in the initial stages of development. With present limitations, it is not workable to replace humans in agriculture.

(k)          Lacks Creativity.  AI machines will do the programmed task only. It cannot improvise or be creative in solving any problem.

The challenges of AI in Agriculture

10.       Building Information Infrastructure.  AI technologies work on the principles of processing the available data. The extensive digitalization of agriculture increases the need for data. There is an inherent need for the collection of a very huge amount of data on all possible fields. It requires creating an infrastructure that gathers and collates data for necessary processing. The establishment of an operative and functional agricultural data management organization. That is the biggest challenge AI have to overcome to establish itself as a functional entity.

11.       Interaction of the connected System.  Piecemeal collection of data at different places will not be of much use. There is a need to connect these independent solutions into one universal organization. This system brings data from one project for all related organisations. The connection of independent systems into one global body and making it function to its best capability is another big challenge.

The Future trends of Artificial Intelligence

12.       The future belongs to AI. Many big technology companies are creating and improving existing technology in this field. Robotics, mobile phone apps, and remote imaging are the main area of advancement in this field. Agriculture is a large industry. It has raises the interest of big technology company to invest in future technology. The main advancements in this field are as follows.

(a)          Mobile Applications.  Many mobile applications are available which connects farmers to the agricultural database. This AI-enabled system helps them in giving information related to all field of Agricultural. These mobile applications offer a range of support. This help from better trading opportunities to regulating and enhancing crop yields.

(b)          See and Spray model.  Technological companies have developed AI machines that can distinguish between plants and weeds. These machines then spray chemicals/herbicides as required. This technology claims to reduce the use of chemicals on crops by 80 per cent.

(c)          Fruit picking System.  Robots have the capability of plucking and picking up fruits from trees. They also have the skills to distinguish between ripe and raw fruits.

(d)          Trimming robots.  Robotic arms with the capabilities to trim vineyards and trees are in existence.

(e)          Solar powered Drones.  Solar-powered drones are proficient in seeing and spraying pesticides and other chemicals.

(f)           Drone Monitoring.  New drones can keep track of a large area of crops. They collect crop data and passes real-time information. It can capture and records images. The build-in sensors differentiate healthy crops from diseased ones.

(g)          Planting Robots.  They can separate seeds and plant them in the fields in the required pattern.

(h)          Image Recognition.  Image processing of pictures captured by drones using image recognition technology. This technology can detect nutrient deficiencies in the soil. It can also detect pests and plant diseases by analysing the photographs. Farmers can use it even on their mobile phones. The apps installed in mobile phones capture the plant’s/soil image. It than analysis the image to identify defects.

(i)           Soil Analysis.  AI-based companies have come up with mobile applications for the analysis of soil. This analysis based on the images of the soil and the crops.

(j)           Precision Farming.  AI-enabled machines today are capable of distinguishing between the crop and the weed. they can also differentiate between ripe and raw fruits. This helps them take precise action on the crops.

(k)          Weather prediction Applications.  These phone applications connect the farmer to Satellite imagery of the area. They analyze climatic conditions likely to prevail in the area and their impact on the crops.

(l)           Computer-Based Assessments.  A very huge amount of database is build up in the computer systems. Companies updates and improves this database regularly. These computer systems examine the images and equate them with the existing database. These systems do real-time analyses of the problem.

Concluding Remarks – AI is the future of Agriculture. The need is to make it accessible to all.

13.       Conventional farming methods will not be able to meet the demand of the population in the future. AI is the only answer to this challenge. The scope of AI in the transformation of agriculture is vast. The technology is developing but still is in the nascent stages. It is expensive and well beyond the reach of most of the farmers. It still has to overcome many challenges to appear as a viable option for a common farmer. There is an urgent need to build up the necessary infrastructure. This infrastructure will make this technology available to all. AI will not remain limited to textbooks.

14.       The range of growth in this field is endless. It is even to the extent of making humans almost completely redundant for farming. Development is needed but development alone is not enough. The technology has to come within the reach of the common farmer. There is a need to educate them about this technology and its advantages. At present most of the farmers in most of the countries have no idea about AI or its applications. The future of agriculture is AI indeed. Its relevance depends on its ability to come out of the books and placed on every farmland globally.

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