Transforming Crop Monitoring System Using IoT and Artificial Intelligence

24 Aug 2022

Farmers are under constant pressure to produce enough food to meet the exponentially increasing demand. Increased cropping intensity and higher yields are required for 90% of the growth in the world's crop production, making the use of agricultural technology techniques and equipment essential for the sector.

The Food and Agriculture Organization (FAO) of the United Nations (UN) reports that the global hunger index climbed from 8.4% in 2019 to 9.9% in 2020, meaning that between 720 and 811 million people experienced acute hunger in that year. The FAO also reported that 2021 saw a record-breaking $1.75 trillion in global food imports, a rise of 14% from the previous year.

Therefore, it is essential to manage damage and infections through primary plant protection to provide the nation's growing population with adequate food security. To give farmers real-time information, smart crop monitoring is essential. This includes soil monitoring, variable-rate technology (VRT), yield and field mapping, and weather forecasts.

This technology can help farmers take the proper steps to decrease crop losses and improve production quality. Smart crop monitoring has emerged using technologies such as the Internet of Things (IoT) and artificial intelligence (AI) is highly beneficial to cater to diverse farming applications such as detecting soil quality, climatic conditions, and crop requirements. 

The impact of smart crop monitoring deployment has ranged from small-scale farming applications like local farm pest management, crop protection, and weeding to large-scale ones like the global remote sensing survey of grassland, forests, and farmland.

Currently, agriculture automation is more prevalent in developed countries attributed to the availability of advanced technologies and equipment. 

However, as smart farming technology can open more prospects for rural farming areas, digital innovation in agriculture technology is becoming more alluring to developing countries. Rural regions that still rely on traditional hand tools can profit from the development of rural infrastructure, supply networks, services, and training.

Additionally, government and regulatory authorities are actively contributing to the growth of the market for smart crop monitoring. For instance, the Chinese government is attempting to modernize the agriculture sector of the nation. The 14th five-year National Strategic Plan for Rural Revitalization was introduced by the Chinese government in 2021.

Under this plan, using "the A-B-C-Ds," or artificial intelligence, blockchain, cloud computing, and big data technology, the government intends to increase the use of smart agriculture. 

As a result, smart crop monitoring is significantly assisting farmers in raising productivity which is leading to significant growth.

According to the BIS Research analysis, the global smart crop monitoring market was valued at $1.92 billion in 2021, which is expected to grow with a CAGR of 12.75% and reach $3.95 billion by 2027.

 AI-Based Transformation in Agriculture Industry

One of the less recognized global industries that have gone digital is the agriculture industry. However, given recent industry improvements, a change is anticipated to be seen as more businesses expand their product offerings by including data collecting, agricultural robotics, and analytic services.

More effective and knowledgeable farming techniques are being implemented thanks to smart farming, which uses cutting-edge technology and IoT to increase agricultural output and operations.

For instance, by creating various components to aid in making farms smarter and more efficient, AI is slated to lessen this high degree of repetitive and physical effort.

The latest techniques and devices employed for crop monitoring using AI in the agricultural industry are as follows:

1.    Agriculture robots: A wide range of equipment, including agricultural robots, have been developed by original equipment manufacturers (OEMs) because of the development of automation and control system designs.

Farming procedures are being reduced because of agricultural robots that specifically detect soil and crops in accordance with their needs. Instead of focusing on the entire farmland with a consistent approach, farming techniques are now more varied for each individual plant. 

Robotic agriculture with minimal inputs fosters a controlled ecological environment, engages in more creative agricultural practices than standard chemical solutions, and reduces resource waste and the ensuing pollution. Rural robots also lessen the need for manual labor, which increases the profitability of farming.

2.    Crop and soil monitoring: The concept of deploying drones in agriculture is well known. Now, farmers can also pre-program the drone's flight path to scan crops using computer vision technology using AI. To record the images for analysis, a universal serial bus (USB) transfer is used. The data is then transferred to a cloud site, where algorithms examine the image crop information.

The software utilized in the cloud can identify any pests, molds, germs, or other health problems that could be affecting a farmer's crops. This technology can scan an average of 50 acres of land in less than 30 minutes and provides farmers with crucial information on their crop yield.

3.    Predictive analysis: This technology is being used by farmers to forecast the weather and evaluate how long their crops will last. Daily weather predictions for news outlets currently use machine learning algorithms from AI technology. These systems provide farmers with the following information:

•    Temperature 
•    Precipitation 
•    Wind speed 
•    Solar radiation 
•    Storm 
•    Drought

4.    Neural sensor farming: The latest innovation in the AI field is neural sensor farming. With the use of this technology, it will be much easier to monitor pests' effects on the agricultural sector and prevent crop infestation and crop health deterioration. In this technology, a brain implant is inserted into the plant seed to monitor or potentially alter behavioural tendencies.

IoT-Based Transformation in Agriculture Industry

The best IoT use in agriculture is precision farming. It can be seen as anything that improves the precision and control of farming practices when it comes to producing livestock and cultivating crops. The employment of IT and numerous tools, including sensors, control systems, robots, autonomous vehicles, automated hardware, variable rate technologies, and other items, is a crucial aspect of this kind of farm management.

The manufacturer's embrace of mobile devices, satellites for images and positioning, and high-speed internet connection are a few essential technologies defining the precision agricultural movement.

This method is being used by several organizations all around the world. For instance, CropMetrics is a company that specializes in managing precision irrigation and is dedicated to providing cutting-edge agronomic solutions.


Due to worries and pressure on the agriculture industry brought on by the rise in global food demand, farmers are compelled to increase farm profitability despite declining yield patterns in several staple crops. 

To overcome these obstacles, growers and the international agricultural sector are relying on technology to transform modern farming into a productive and automated crop production process. Smart farming is an emerging phenomenon to increase farm output that involves crop monitoring using AI and IoT.


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