Showing posts with label Intelligent Sensing. Show all posts
Showing posts with label Intelligent Sensing. Show all posts

Artificial Intelligence - Agriculture Using Intelligent Sensing.


From Neolithic tools that helped humans transition from hunter gatherers to farmers to the British Agricultural Revolution, which harnessed the power of the Industrial Revolution to increase yields (Noll 2015), technological innovation has always driven food production.

Today, agriculture is highly technical, as scientific discoveries continue to be integrated into production systems.

Intelligent Sensing Agriculture is one of the newest additions to a long history of integrating cutting-edge technology to the production, processing, and distribution of food.

These technological gadgets are generally used to achieve the dual aim of boosting crop yields while lowering agricultural system environmental effects.

Intelligent sensors are devices that, as part of their stated duty, may execute a variety of complicated operations.

These sensors should not be confused with "smart" sensors or instrument packages that can collect data from the physical environment (Cleaveland 2006).

Intelligent sensors are unique in that they not only detect but also react to varied circumstances in nuanced ways depending on the information they collect.

"In general, sensors are devices that measure a physical quantity and turn the result into a signal that can be read by an observer or instrument; however, intelligent sensors may analyze measured data" (Bialas 2010, 822).

Their capacity to govern their own processes in response to environmental stimuli is what distinguishes them as "intelligent." They collect fundamental elements from various factors (such as light, temperature, and humidity) and then develop intermediate responses to these aspects (Yamasaki 1996).

The capacity to do sophisticated learning, information processing, and adaptation all in one integrated package is required for this feature.

These sensor packages are employed in a broad variety of applications, from aerospace to health care, and their scope is growing.

While all of these applications are novel, the use of intelligent sensors in agriculture might have a broad variety of social advantages owing to the technology.

There is a pressing need to boost the productivity of existing productive agricultural fields.

In 2017, the world's population approached 7.6 billion people, according to the United Nations (2017).

The majority of the world's arable land, on the other hand, is already being used for food.

Currently, over half of the land in the United States is used to generate agricultural goods, whereas 40% of the land in the United Kingdom is utilized to create agricultural products (Thompson 2010).

Due to a scarcity of undeveloped land, agricultural production must skyrocket within the next 10 years, yet environmental effects must be avoided in order to boost overall sustainability and long-term productivity.

Intelligent sensors aid in maximizing the use of all available resources, lowering agricultural expenses, and limiting the use of hazardous inputs (Pajares 2011).

"When nutrients in the soil, humidity, solar radiation, weed density, and a wide range of other factors and data affecting production are known," Pajares says, "the situation improves, and the use of chemical products such as fertilizers, herbicides, and other pollutants can be significantly reduced" (Pajares 2011, 8930).

The majority of intelligent sensor applications in this context may be classified as "precise agriculture," which is described as "information-intensive crop management that use technology to watch, react, and quantify crucial factors." When combined with computer networks, this data enables for field administration from afar.

Combinations of several kinds of sensors (such as temperature and image-based devices) enable for monitoring and control regardless of distance.

Intelligent sensors gather in-field data to aid agricultural production management in a variety of ways.

The following are some examples of specialized applications: Unmanned Aerial Vehicles (UAVs) with a suite of sensors detect fires (Pajares 2011); LIDAR sensors paired with GPS identify trees and estimate forest biomass; and capacitance probes measure soil moisture while reflectometers determine crop moisture content.

Other sensor types may identify weeds, evaluate soil pH, quantify carbon metabolism in peatlands, regulate irrigation systems, monitor temperatures, and even operate machinery like sprayers and tractors.

When equipped with sophisticated sensors, robotic devices might be utilized to undertake many of the tasks presently performed by farmers.

Modern farming is being revolutionized by intelligent sensors, and as technology progresses, chores will become more automated.

Agricultural technology, on the other hand, have a long history of public criticism.

One criticism of the use of intelligent sensors in agriculture is that it might have negative societal consequences.

While these devices improve agricultural systems' efficiency and decrease environmental problems, they may have a detrimental influence on rural populations.

Technological advancements have revolutionized the way farmers manage their crops and livestock since the invention of the first plow.

Intelligent sensors may allow tractors, harvesters, and other equipment to operate without the need for human involvement, potentially altering the way food is produced.

This might lower the number of people required in the agricultural industry, and consequently the number of jobs available in rural regions, where agricultural production is mostly conducted.

Furthermore, this technology may be too costly for farmers, increasing the likelihood of small farms failing.

The so-called "technology treadmill" is often blamed for such failures.

This term describes a situation in which a small number of farmers adopt a new technology and profit because their production costs are lower than their competitors'.

Increased earnings are no longer possible when more producers embrace this technology and prices decline.

It becomes important to use this new technology in order to compete in a market where others are doing so.

Farmers who do not implement the technology are eventually forced out of business, while those who do thrive.

The use of clever sensors may help to keep the technological treadmill going.

Regard less, the sensors have a broad variety of social, economic, and ethical effects that will need to be examined, as the technology advances.


Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.

See also: 

Workplace Automation.

Further Reading:

Bialas, Andrzej. 2010. “Intelligent Sensors Security.” Sensors 10, no. 1: 822–59.

Cleaveland, Peter. 2006. “What Is a Smart Sensor?” Control Engineering, January 1, 2006.

Noll, Samantha. 2015. “Agricultural Science.” In A Companion to the History of American Science, edited by Mark Largent and Georgina Montgomery. New York: Wiley-Blackwell.

Pajares, Gonzalo. 2011. “Advances in Sensors Applied to Agriculture and Forestry.” Sensors 11, no. 9: 8930–32.

Thompson, Paul B. 2009. “Philosophy of Agricultural Technology.” In Philosophy of Technology and Engineering Sciences, edited by Anthonie Meijers, 1257–73. Handbook of the Philosophy of Science. Amsterdam: North-Holland.

Thompson, Paul B. 2010. The Agrarian Vision: Sustainability and Environmental Ethics. Lexington: University Press of Kentucky.

United Nations, Department of Economic and Social Affairs. 2017. World Population Prospects: The 2017 Revision. New York: United Nations.

Yamasaki, Hiro. 1996. “What Are the Intelligent Sensors.” In Handbook of Sensors and Actuators, vol. 3, edited by Hiro Yamasaki, 1–17. Amsterdam: Elsevier Science B.V.

What Is Artificial General Intelligence?

Artificial General Intelligence (AGI) is defined as the software representation of generalized human cognitive capacities that enables the ...