With the accelerating growth of the global population, the resulting increase in global food consumption, dwindling agricultural areas, and the depletion of scarce natural resources, improving farm production has become crucial.

The situation has been exacerbated by a lack of natural resources such as fresh water and fertile land, as well as declining production patterns in key main crops. The changing composition of agricultural labor is another major worry for the farming business.

Furthermore, agricultural work has decreased in most countries. The use of automated systems in farmers has been spurred because of the diminishing agricultural workforce to lessen the demand for manual labor.

Precision agriculture (PA) is a farming management approach centered on detecting, measuring, and reacting to grain variability both within and between fields. Precision agriculture research aims to develop a decision support system (DSS) for the whole administration that maximizes input returns while conserving resources.

Leading agriculture machinery producers and technology suppliers are proposing unique solutions in the farming sector to handle the rising demand for food from restricted farmlands and manpower.

These solutions are aimed at assisting farmers in closing the supply-demand imbalance by providing a high yield, greater profit, and environmental preservation.

Precision agriculture is a method of employing information technology (IT) to assure the most efficient use of resources to produce high crop yields and lower operating costs. Precision agricultural technologies include specialized machinery, software, and information technology services.

The lack of network availability in rural locations is a key drawback. Farmers are always concerned that their agricultural data may be shared with the public or rivals.

The lack of defined legislation and regulations to prevent third-party exploitation further limits the precision agricultural market’s expansion. Precision agriculture creates a large quantity of data, which might lead to security concerns.

There are questions about who owns the data, how it will be used, and how the firms would keep it. While many farmers handle data in a digital format, a sizable proportion of farmers are hesitant to share their data with firms that would provide precision agricultural solutions.

Precision agricultural technology has been transforming the way farmers administer their crops in the past. The value addition it provides to all farmers in overcoming difficulties such as labor shortages, climate change, farm management, and agriculture companies in the sector is the key driving factor behind its expanding acceptance.

Emerging technologies in Precision Agriculture

Precision agriculture is a form of digital farming that uses cutting-edge technology.

• Robots

Self-steering tractors, such as John Deere machinery, have been around for a while and function similarly to an Aeroplan on autopilot. The tractor executes most of the job, with the farmer stepping in only in the event of an emergency.

Self-driving cars controlled by GPS to spread fertilizer or plow land are becoming a reality. Solar-powered equipment that detects weeds and eliminates them precisely with a dosage of pesticide or lasers is among the other inventions.

• Drones and Satellite Imagery

Precision farming makes use of drone and satellite technologies. When drones shoot high-resolution photographs while satellites record the overall view, this happens frequently.

Given the current levels of agricultural biomass, aerial photography from light aircraft may be paired with data through satellite records to anticipate future yields.

Convoluted pictures may be used to make contour maps, which can be used to monitor where water flows, estimate variable-rate seeding, and construct yield maps of productive regions.

• The Internet of Things

The Internet of Things (IoT) is an internetworking of physical devices that have been equipped with technology to allow data gathering and aggregation.

With the introduction of sensors and farm management software, the Internet of Things comes into play. Farmers can, for example, use spectroscopy to determine the levels of nitrogen, phosphorous, and potassium in liquid manure, which is notoriously unreliable.

They may then assess the ground for areas where cows have already urinated and fertilized, just those areas that require it. This reduces fertilizer usage by up to 30%. The optimal times to water plants remotely are determined by moisture sensors in the soil.

• Smartphone Applications

Precision agricultural apps for smartphones and tablets are becoming increasingly popular. Many important programs, such as the camera, microphone, GPS, and accelerometer, are already loaded on smartphones.

There are additional apps specialized to specific farm applications, such as field mapping, animal monitoring, climate and crop information, and so forth.

• Machine Learning

Drones, robots, and Internet of Things devices are frequently utilized in combination with machine learning. It permits information from each of these sources to be entered.

This information is subsequently processed by the computer, which then sends the relevant actions back to these devices. This enables robots to precisely provide the right amount of fertilizer or IoT devices to precisely give the right amount of water directly to the land.


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