Artificial Intelligence (AI) in economic growth plan

Introduction

By 2050, The Global population is predicted to increase even more than one billion people, which is putting pressure on about a 70% increase in agriculture products. It is necessary to meet the increasing demand to feed the hungry people. Only around 10% of this extra production might come from the availability of?vacant lands, while the remaining 90% should be fulfilled by introducing improvements in the current production technologies. In this regard, one of the most pressing needs is the application of cutting-edge Technology Solutions to provide farming efficiency. Current agricultural intensification tactics necessitate significant energy inputs while the market is in demand of high-quality commodities. The capacity of labor and the rising cost of labor?is a campaign by crop failures?which are the driving factors of decreasing production of Agricultural commodities. Moreover, other environmental and climatic factors include disease and pest attacks, lack of rainfall, variations in the climatic conditions, e.g., temperature, humidity, etc., and loss of soil fertility, are the main reasons for fluctuations in production and market prices. This imposes a negative impact declining the socio-economic status of the country. Along with financial?decrease, the point of concern is that there is an increasing demand for Agricultural Products with time, but current technology has failed to meet the demand (Popa, 2011). To meet the increasing demands of the increasing population, there is a necessity to develop smart farming practices especially featuring artificial intelligence, to reduce the economic losses and increase productivity. Through artificial intelligence, different platforms can be developed which will have the ability to collect large amounts of data from different public and government websites. This will also provide real-time monitoring of various data sets through the incorporation of IoT (Internet of Things). This data can be used for accurate analysis to help the farmers address various issues responsible for the fall of agriculture production. According to the United Nations, two-thirds of the world's population will reside in cities by 2050, which will be responsible for diminishing the workforce, especially in rural areas or agricultural lands. To relieve the workload from the farmer’s new technologies will be required to perform farm operations. By introducing?and incorporating the technology, farmers will be able to operate the farms remotely, different field operations can be automated, different risks can be identified timely, and the concerns of farmers regarding reduced production can also be decreased. However, for this purpose, the farmers will also need to develop abilities that will be a combination of both technology and Biology skills instead of the previously needed agricultural skills.

Importance of artificial intelligence in agriculture

Artificial intelligence has the ability to be applied in various disciplines as it is now introducing a paradigm shift?from previous traditional cultural practices to modern farming. Different solutions powered by AI?will allow the farmers?to utilize less input and receive greater output and will?also be responsible for an increase in the quality of the crop?in a time-efficient manner. The efficiency of time by speeding up the farm operations will allow the product to reach the market faster, which will then be delivered?to the consumers. Artificial intelligence, Big data, and?the internet of things are becoming Significant determinants for offering digital IT?solutions in?practically all professions and business sectors (Channe, Kothari & Kadam, 2015).?As a result, there is a need to deploy a Digital solution that can help the farmers in innovating their farm operations with the help of artificial intelligence. It will also be used to uplift the status of the farmer community and directly or indirectly will provide an increased potential for businesses and entrepreneurs as smart farming has the ability to meet the increasing demands of the market (Bannerjee et al., 2018).?

Growth was driven by the internet of things (IoT)

The world of agriculture is being developed and transformed with the introduction of digital technologies. IoT?Technology enables the linkage of structured and unstructured data for the provision and insight of production Technologies. With the help of IoT, massive amounts of?unstructured and organized data are generated on a regular basis. These data sets include valuable information, which usually includes the history of the weather patterns, soil?analysis and its reports, updated research, levels of rainfall, an infestation of pests, and pictures taken from the drone cameras. All of these data sets can be easily sensed and organized by the installation of cognitive IoT?solutions, which can then deliver actionable insights to increase the productivity and yield of agricultural lands. The most common technologies used for the combination of the data through artificial intelligence include remote sensing and proximity sensing. Soil testing is one of the applications for the?achievement of high-resolution data (Paventhan et al., 2012). While through Remote Sensing, integration of different sensors into aerial or satellite systems can be done. Proximity sensing necessitates the sensors, which are ground-based and need direct contact with the ground. The proximity sensors are usually low-range sensors. They are very helpful in providing aid for the classification of the soils, which majorly depends upon the soil located under the surface at a specific location.?Other hardware solutions, including the robots, are already in action for combining data collection software with robotics to produce and generate appropriate fertilizers given to the crops. The robots equipped with different sensors can also perform different farm operations, which are necessary for maximizing the agricultural output. To increase the efficiency of the IoT, there is a necessity to place the sensors at specific locations around the field. The senses of specified in transmitting and capturing the data which is based on the weather conditions, moisture of the soil and fertility, growth of root and shoot systems, vigorous growth of leaves, surveillance of photoperiods, setting off flowers and seeds, bearing of fruit, detection of the infestation of different insects and diseases and the harvesting time (Suma et al., 2017).?

The transducer in IoT devices probes various environmental and crop factors, which are explained above.?These sensors can be easily installed?on tiny protected boards that are connected to a Wi-Fi device, microprocessor, VGA?image sensor with low cost, and a micro solar panel power Mini battery. By installing these devices, the primary data can be collected at predetermined times by erecting the active Wi-Fi hotspot, which can cover the whole field. Drones having an active Wi-Fi?connection can also be used to Gather and scan the data from IoT?devices installed at various places in the field. This can also be used to create a high-resolution motion picture that will entail all the details of the entire field (Suma et al., 2017).?

Data-driven farming

After incorporating and integrating artificial intelligence in the farming system, the farmers will be able to make more precise decisions through the analysis and linkage of information received from this technology. Different types of pieces of information, including climate, types of seeds, quality of soil, disease and pest infestation race, the pattern of the market, and prices, can be readily available for the farmers to make decisions (Yang et al., 2012).

Generation of image-based insight?

Considering the current technological evolution and its introduction in the agricultural field to see and farming can be considered as one of the most discussed and debated areas in this sector.?Photos taken by the drones assist with the analysis of the field in-depth, monitoring of the crops, scanning the fields, and other related tasks to the farming.?Farmers can use a combination of different computer vision Technologies, IoT, and drones to shore quick responses.?Drone image data feeds can create real-time?alerts, which helps in speeding up the process of Precision farming.?Arial drones, for example, have integrated the IBM?Watson IoT?platform and visual recognition into commercial drones (Patrício & Rieder, 2018).

Following are the areas where the technology of computer vision can be used.

Detection of disease: The leaf photos are split into areas such as background, parts of the non-diseased area, and diseased areas after preprocessing.?After that, the infected area is clipped then sent to distant laboratories for further analysis. This technique also helps in the identification of the pests, nutrient deficiency in the plants, and various other stresses which can hinder the field of the?plant.?

Crop Readiness identification:?

under the white. UV-A light images of various crops are collected to determine the ripening of green fruits. Before shipping the crop to the market, farmers will have several options to develop various levels of readiness, which will be based upon the crop or the fruit category while staking them separately.

Field management:?by developing a field map and identification of the places where the crop systems need irrigation, any fertilizer, or pesticides, real-time estimations can be created.?During the time frame of cultivation, utilization of high definition photographs taken from the airborne systems, more probably from the drones, can provide this real-time estimation.?This significantly adds to resource optimization.??

Identification of the?product mix of the best agronomic sector

Cognitive solutions give the suggestions to the farmer which are crop specified.?These suggestions can revolve around the selection of hybrid seeds after detecting the quality and condition of the soil, environmental conditions, climatic forecast, the types of?seeds, and the nature of infestation at a specific location and conditions. After the analysis of these abiotic factors, this advice given by artificial intelligence can further be customized on the basis of the needs of the farms?considering the local conditions and historical data to present successful automated farming.?Farmers may also consider external elements, including the trend set in the market, ups and downs of prices, and demand of the consumers in order to make an appropriate decision which will lead to improved yield and financial status.

Health monitoring of the crop

To develop crop metrics?across thousands of acres, there is a need for high-end technology that will be based on remote sensing, hyperspectral imaging, and 3D laser scanning. These technologies have revolutionized the agricultural sector because of their potential to bring about a fundamental shift and give innovation to the farmers regarding the monitoring of fields in terms of both time and effort. Similar technology can also be used for tracking the crops during their holiday distance along with the generation of the reports in the event of anomalies.

Irrigation automation techniques and farmer empowerment

?irrigation is one of the most important for my activity and is one of the most laborious and intensive operations in agriculture.?Irrigation can be automated, and the total productivity can be increased by using different machines and technological solutions that are trained on the basis of past weather patterns, soil conditions, and the types of crops which are constantly being cultivated in that particular area. Irrigation uses?over 70% of the total world's fresh water; therefore, automation is necessary for two reasons. One of the main reasons is saving the water, which is extensively used in agriculture practices, while the other reason includes optimization and automation of the farmland. Automated irrigation techniques will not only help the farmers to avoid laborious irrigation but also help the farmers in the better management of the water challenges which are at the global level (Gondchawar & Kawitkar, 2016).

Use of drones with the incorporation of artificial intelligence in agriculture

Agriculture is one of the most promising sectors which is promoting the use of bronze to deal with the potential risks and challenges while optimizing the practices. Because of the introduction and extensive use of drone technology, this factor of agriculture is having a high-tech makeover. Following are the fields by which drone technology can be used for the optimization of yield throughout the crop cycle.?

Field and soil analysis:?

the utilization of drone Technology helps in the production of precise 3D maps, which helps in the early hours of the soil. Drones also play an important role in Planning the seed planting and gathering the data regarding nitrogen levels among the plants and irrigation.

Planting:?

modern technology has Now introduced Drone planting systems. Planting the seeds of seedlings in the field used to be a laborious and time-consuming method. It required the involvement of labor with expertise. Now the Drone planting systems can automatically shoot the pods with the seeds, and optimum levels of the nutrients are maintained in the soil.?While planting the seeds, it is made sure that there are sufficient nutrients?to facilitate the growth of a plant and overall crop.?

Crop spraying:?

drones are equipped with sensors that are able to scan the ground and start spraying?in the field. This approach can be the incorporation of pesticides or fertilizer in real-time to obtain and even coverage. Aerial spraying is considered five times more effective when it is incorporated with drone technology as compared to the traditional method where labor is required.?

Monitoring of the crop:?

mostly monitoring is a tough, laborious, and time-consuming action that requires expertise.?However, this process is also technical because, during monitoring, there are many chances of a prevalence of human error.?Mostly?the damaging parts?or stressed conditions of the plants are overlooked, increasing the chances of reduced yield. However, with the help of Drone Technology, there is a high possibility of the proper assessment and monitoring of the crop with the help of time series animations which can represent the proper development of a crop.?It also has the ability to reveal production inefficiencies and can also suggest better management tactics which can be helpful in elevating the shield of the crop.?

Irrigation:

Sensor drones can detect different areas of the field in order to monitor whether the field is in need of irrigation or not. If any part of the field is considered dry, then The sensors detect it and start irrigation.

?Assessment of the health of crops:

Drone carried gadgets can assist track changes in the plants, show their health, and make an alert to the farmers regarding the illness of the crops by scanning a crop through the use of visible and infrared light. There is a probability that UAVs can be made up of self-contained forms of drones, which will be used for the collection of the data and performance of the jobs which used to be done by the labor. The most significant impediment to this becoming a reality is the lack of sensors that are capable of collecting the data in high quality and the software which is capable of collecting statistical data. It is necessary because by collecting the necessary data, the farmlands can be revolutionized where there will be less requirement of labor because of automation and accurate prediction.

?Different models can be used on the farms to provide services to the farmers.

The use of artificial intelligence in the automation and mechanization of farms is now a reality because currently, there are various areas where artificial intelligence is being used. Following are the technologies that can be used in the future in the agriculture sector.

Chatbot

Chatbots powered by artificial intelligence, which is also called virtual assistants, are currently being employed in the retail, media, insurance, and travel industries. The agriculture sector can benefit from this technology. For example, the Chatbot should be area-specific where they should be able to answer the common problems which the farmers Might confront and seek answers to.?Those answers should be programmed in the Chatbot. Then this Chatbot will be placed to help the farmers by providing them answers to their questions and issues and advice for specific challenges. This program allows the farmers to get answers to the questions via interactive voice chat, which will be in their native language to avoid language barriers. For ongoing and context-sensitive learning, Chatbot can be used to supervise and reinforce machine learning algorithms. As a result, the Chatbot responds to the majority of the general questions which were already programmed to be answered.?It will automatically reduce the burden on the human operators and save the time of the farmers as well because Chatbot will be available to respond to their requests which are general in nature. At the same time, the human operators will only be contacted when there is a problem for the farmers, which is unique, and seek human assistance.

Agri-E-calculator

The agri-e-calculator is one of the examples of artificial intelligence, which is actually a smart application that is used to assist smart farmers in the determination of the most appropriate crop. It also helps the farmers in choosing affordable crops according to a variety of parameters. The farmers can select the needed crop which will be cultivated Across their specified form coverage area with the help of this smart calculator. The E-calculator then automatically recognizes and takes all the necessary and required inputs.?While taking inputs, the calculator also considers the dependency of these inputs on different variables.?By doing this e-calculator calculates and offers the estimated results. The outcomes, which can also be considered as the outputs, include information on different crop parameters, which usually include?cost and quantity of fertilizers, the need for irrigation, variety and amount of seeds, cost of labor, and that of labor by distributing on a calendar chart. This also helps in making a crop life cycle, expected yield of the crop, and extrapolated market price at the time of harvest. This calculator is beneficial because it can also provide an estimation of the profitability by considering the cost of inputs?throughout the crop season. This calculator not only depends on the external?data, which is generally taken from the government websites but also?develops a farmer’s database. By combining both types of data, this calculator makes estimations. This calculator can be used for the collection of the data?in both linear and nonlinear form to give the estimation of the outputs. In order to?make an estimation of the outputs, machine learning approaches process the inputs and give an estimation with the use of feasibility analysis. With different types of crops and other inputs, the farmers will have the choice to select the desired crop because estimation?of the output will be given by e-calculator?allowing the farmers to make a decisive and wise choice for the selection of the crop for cultivation.

Crop Care Service

From seed growth through harvesting, the Crop Care Service guidance encompasses the entire process. Artificial intelligence Algorithms are used for the analysis of complex structure data. This data is obtained from IoT sensors that are installed in the fields. The data is also taken from different sources, which include Government and public websites, information sites, and main export contributions. All of this data is collected, and it is saved in the artificial intelligence algorithm, which is responsible for Crop Care Services when there is a need for the analysis of the data. The overall corrective action item is derived from the controller mechanism based on Proportional integral and differential controller (PID). This system is approached after the processing of all the data obtained from different sources, including the data from installed sensors in the field, different websites, and observations. As a result, the farmer receives an alert on their smartphones (Zhu et al., 2014). This alert allows the farmers to understand the situation of their field. It also prompted them to priorities certain corrective actions which need urgent attention because of the severity and urgency of the situation.

Guidance of the market and prediction of the prices

Farmers can benefit from this service because this service can protect them from the fluctuations of the market. It can also reduce the dangers of a price loss, which is the most common concern of the farmers. These days’ fluctuation of prices in the market is one of the biggest hindrances and challenges for the farmers because of which most of the farmers rely on the traditional cropping pattern because it ensures them a certain amount of profit.?Now, considering the farming patterns, it is suggested to The cropping pattern because there are many crops which can benefit. Nevertheless, due to the lack of a proper market and fluctuations in prices, the farmers are hesitant and reluctant to cultivate those crops. Nevertheless, through this service, there is a high probability of understanding the fluctuations in the market and the ups and downs of prices. With the help of this application, the farmers can predict the pricing and understand the demand information, which will be based on the statistical data during the whole crop lifetime. This statistical data can be obtained from different sources considering previous history, the demand of the particular crop, ups and downs of that crop, and price fluctuation. After receiving this information, the farmers will have the ability to arrange better and understand the patterns by which they can release their agricultural products to the market.

Service for crop loans and insurance

This service can assist performers in determining the viability of obtaining a loan on the crops. Usually, the farmers holding small farmland areas do not have enough resources to stabilize themselves financially. Moreover, during the cultivation of a crop, there is a handsome amount of money involved in the farm operations. The majority of the farmers are unable to automate their form because of their limited financial resources. With the help of the service, the farmers can pursue the application for a loan. This application will help in obtaining loan processing assistance, eligibility criteria, and a loan limit according to the smart estimation for the proposed crop. It can also help in getting the crop insured as a contingency plan in case of crop failure due to unforeseen events or disasters, for example, changes in the climatic pattern.

Current applications of artificial intelligence in the agriculture sector

Blue-river Technology

In 2011 this company was established. This is a California-based company that represents a combination of artificial intelligence, computer vision, and Robotics for the creation of next-generation agricultural equipment. The purpose of this combination is to produce and develop a technology that can help the farmers in automation of their farmlands and reduction of labor. This is also aimed at saving money, making time-efficient gadgets to save time, and lowering chemical uses. In this, computer vision recognizes every individual plant and determines its treatment. Robotics allows smart robots to perform farm operations according to the assessment. For example, if harvesting is needed of a particular fruit in an orchard, then the robotics are the ones who will be responsible for the harvesting of the fruit considering the program in which they analyze the estimation of crop growth, color, and age of the fruit. The sensors can be installed at different places in the field, which can then be used for the detection of the weeds, the types of weeds that need to be pulled out, and the detection of the appropriate herbicides. It is necessary to use proper herbicide because of the similar nature of both the plants, including weeds and crops. If there is an error in choosing herbicide, it may damage our main crop.?Moreover, considering the environmental conditions, it is also necessary to choose an herbicide with a less environmental hazard. The choice of herbicide is also important as it should create an appropriate buffer around the plant. Machine learning is used in the cameras and sensors where the images are collected.?For this purpose, machines can be taught in a variety of ways through the installation of concerning algorithms. The correct type and amount of herbicides are then sprayed precisely according to the invasion area. One of the examples of this combination represented by fluid technology is See & Spray, which is a robot. It is said to use computer vision for the monitoring and accurate spraying of the weeds around the cotton plants. Herbicide resistance can be avoided by a precise tray of herbicides.

Farm Bot

This company has started considering precise farming and took it to a new level by allowing environmentally aware consumers to cultivate crops on their own land using Precision farming Technologies. Farm Bot is a device that allows owners to do end-to-end farming on their own. Agri farming practice is taken care of by the physical what which utilizes an open-source software system from the first to the last stage of the crop, i.e., From seed planting to the detection of weed and soil testing to irrigation requirement of the plants.

Plant diseases diagnosis

There is an app that is developed with the name Plantix. This application is able to detect the probable flaws and nutritional deficits, especially in the soil. This program uses different photos for the detection of the problems and disease issues occurring in the plants.?In this, the photographs are taken with the help of a smartphone which is then matched with a server image, and a plant health diagnosis is delivered. This application solves issues related to plant disease with the incorporation and utilization of Artificial Intelligence and machine learning.

Challenges with incorporation and utilization of artificial intelligence in the agriculture sector

Despite the fact that artificial intelligence has a wide range of applications in the agriculture sector, there is still a lack of formality with high-tech?machine learning solutions at most farms throughout the world. Farming is highly exposed to environmental elements, which usually include climatic conditions, soil conditions, and the existence of pests, including insects and disease-causing agents. So what may appear to be a reasonable answer at the start of harvesting may not be the best option due to changes in various external factors.

In order to train robots and produce exact predictions, artificial intelligence systems require a large amount of data. Though spatial data can be easily acquired?in the case of a huge agricultural area, temporal data is difficult to come by. Most crop-specific data, for example, can only be gathered once a year when the crops are growing.?Because data infrastructure takes time to grow, it takes a long time to?develop a reliable machine learning model. This is one of the main reasons that artificial intelligence is more commonly used in agronomic items like seeds, insecticides, fertilizers, and other electronic products instead of its installation for the precise solutions of agricultural fields (Dharmaraj & Vijayanand, 2018).

AI for Smart Cities

It is considered that smart cities and artificial intelligence will take our major cities and develop towns in the next 50 years.?This will happen throughout the world because artificial intelligence will play an important role in dictating The living of human beings and machines or other Technologies. This will bring out better experiences along with more safety and ease. A smart city is considered a highly sophisticated city and incorporates information along with communication technologies to improve the quality of life of human beings.?It also tries to improve the performance and effectiveness of urban spaces, including various other domains, for example, transportation and energy public resource wastage and reduction of the overall cost for or the management of the smart cities. All these goals can be achieved by incorporating artificial intelligence, which can be done by incorporating the internet of things. A smart city can generate vast data sets which can contribute to learning situations. It also allows the Machines to make correct decisions by incorporating cloud computing, sensor network, and the combination of the internet of things. The incorporation of artificial intelligence for the development of smart cities can help in improving harmony, reducing waste and carbon footprints. It can also help in strengthening communication and maintaining security for the safety of people.

Artificial intelligence in FinTech and blockchain

?different financial firms are constantly struggling to adopt modern technology, which helps the fintech companies solve the problems. Artificial Intelligence can be incorporated to improve the results. Different fintech companies have allowed different technological features, for example, artificial intelligence, Big Data Analytics, evolutionary algorithms, to introduce improvements. Artificial Intelligence can help fintech companies in making accurate decisions. It can also help in generating automated customer support. It can also help in the determination and detection of different types of fraud. The evidence can be collected through the Analytics tool, which can provide enough material for the conviction. There is various automatic virtual financial assistance in fintech and blockchain, which help make financial decisions by monitoring history, different events, and stock rates.

In the blockchain, large amounts of processing power are required. Artificial Intelligence can provide opportunities to deal with the tasks in intelligent and efficient ways with the incorporation of machine learning-based algorithms, which can provide and polish the skills by incorporating appropriate data sets. The incorporation of artificial intelligence in blockchain technology allows the protection of the data. The data sets that include medical or financial data are often considered sensitive; therefore, it is necessary to have an option to protect data. The incorporation of artificial intelligence can protect the storage of search data on the blockchain. The incorporation of artificial intelligence in the blockchain is an undiscovered area that needs more attention to create a line that can help human beings increase their efficiency.

Conclusion

Modern technology, especially artificial intelligence, has assisted the farmers in analyzing the land, health of the crops, soil analysis, and various other factors.?This technology has helped the farmers in saving their time and labor costs.?Moreover, it also has resulted in helping the farmers to grow the optimum harvest for each season.?Vertical cropping can save water, make better use of land, and be grown in buildings in Metropolitan settings. It also has the potential to elevate labor shortages.?This can be done by the incorporation of artificial intelligence in the vertical cropping system where a person can avail fresh produce on their own.?There are various applications of artificial intelligence which also include the production of the seasons of the crops, weather, climatic conditions, and optimum rainfall for the following year. Forecasts which are based on artificial intelligence allow for the Recommendation of the appropriate pesticides, suitable crops according to the land and valuable inputs, locations that can be prepared for cropping at the proper moment, and prior alerts of disease or pest infestation after the analysis of patterns of the previous years at a big scale. There is also a huge opportunity for the agriculture and industry to leverage the emerging technology of catboats which are available to assist the farmers with all their queries.?They are also available for giving relevant advice and recommendations. These recommendations are specific because the technology takes specific form related problems and recommends the solutions by considering other abiotic and biotic factors. Automatic response systems can also be used in agriculture with huge space, especially the areas which are still in touch in this sector. Artificial intelligence has the capability to penetrate the agriculture sector because of its various benefits. There are various applications of artificial intelligence in agricultural lands which has resulted in better use and reduced the labor cost along with time. Considering these benefits, it can be concluded that the agricultural sector can utilize artificial intelligence for almost every farm operation, including the estimation of the market and fluctuations of prices which usually concern the farmers. It has made its way in almost every operation that can enhance the production and yield in the agriculture sector.