Introduction

Smart farming is a management concept that gives the agricultural industry the framework to grasp advanced applications – containing extensive information, the cloud, and the internet of things (IoT) – for following, observing, self-operating, and examining actions under IoT solutions. 

Smart farming is rising in importance due to the increasing worldwide population, the rising demand for excessive crop yield, the requirement to use natural resources expertly, the increasing use and composure of information and interaction technology, and the rising requirement for climate-smart agriculture under IoT solutions.

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Smart farming techniques

Smart farming includes the utilization of techniques such as:

• Sensors are used for soil scanning and water, light, humidity, and temperature management.

• Telecommunications – Technologies such as advanced networking and GPS.

• Hardware and software are used for specific automation. And for allowing IoT-based solutions, robotics, and automation.

•  Data analytics tools are used for decision-making and divination. Data collection is a significant part of Smart farming as the quantity of data available from crop yields, soil mapping, climate change, fertilizer applications, weather data, machinery, and animal health continues to expand under IoT solutions.

• Satellites – Satellites, and drones gather information around the clock for an entire area. This data is delivered to IT systems for tracking and examining to give an “eye in the field” that makes remote monitoring practicable.

The combination of these technologies facilitates machine-to-machine derived data. 

For example, by explicitly measuring variations within a field and adapting the strategy accordingly, farmers can significantly enhance the validity of pesticides and fertilizers and utilize them more sensibly.

Similarly, Smart farming technology assists farmers in better observing the requirements of individual animals and balancing their nutrition to avoid disease and increase herd fitness under IoT solutions.

Advantages of Smart farming are:

• By creating farming more associated and intelligent, precision agriculture helps decrease overall costs and enhance the quality and quantity of products, agriculture’s sustainability, and customer experience under IoT solutions.

• Expanding control over construction leads to better cost management and waste reduction.

• The potential to detect anomalies in crop growth or livestock health, for instance, assists abolish the possibility of losing yields. Additionally, automation increases efficiency under IoT solutions.

• With smart devices, multiple processes are activated simultaneously, and automated services enhance product quality and volume by better controlling production processes.

• Innovative farming systems also allow the careful charge of the demand prediction and transfer of goods to market just in time to decrease excess under IoT solutions.

• Precision agriculture is based on controlling the supply of land and, based on its condition, concentrating on the suitable growing parameters – for example, moisture, fertilizer, or material content – to produce the right crop in the application.

• The various precision farming systems implemented depend on software to manage the trade under IoT solutions.

Facts about smart farming:

• Smart farming and IoT-driven agriculture are assigning the groundwork for a “third green revolution,” which mentions the integrated application of data and communications techniques under IoT solutions. It includes devices such as precision equipment, IoT sensors and actuators, geo-positioning systems, crewless aerial vehicles, and robots.

• IoT technology helps control agriculture processes to reduce production risks and enhance the ability to foresee production results, allowing farmers to plan better and distribute the product under IoT solutions. Data about identical batches of crops and the number of crops to harvest can help farmers cut down on labor and waste under IoT solutions.

• Smart farming established on IoT technologies allows growers and farmers to decrease excess and increase fertility fluctuating from the aggregate of fertilizer appropriate to the number of journeys the farm vehicles have made and authorizing systematic utilization of resources such as water, electricity, etc.

• IoT Smart farming solutions is a system built for observing the crop field with the help of sensors and automating the irrigation system under IoT solutions.

Importance of smart farming for agriculture:

About 15% of farmers are utilizing Smart farming techniques as a consequence. That’s not an IoT, but Smart agriculture will become more integral in several decades.

We require smart farming to:

• Improve crop health – Optical Smart farming technologies allow farmers to identify crop diseases and other problems earlier.

• Reduce the ecological footprint of farming – Precision agriculture systems can reduce the use of harmful chemicals and carbon emissions under IoT solutions.

• Help feed the increasing global population – The UN data shows that the world’s population will increase from 7.7 billion in 2020 to 9.7 billion in 2050.

• Providing food security in climate change scenarios – More efficient smart farming helps adapt to changing climates while maintaining production levels under IoT solutions.

• Achieve higher yields while reducing operating costs – Smart farms achieve higher results and lower energy costs.

The IoT-Based Smart farming circle

The key to IoT is the information you can draw from things and transfer over the internet. To develop the farming procedure, IoT appliances established on a farm should assemble and process information in a continual cycle that allows farmers to respond immediately to growing problems and changes in context situations under IoT solutions. Smart farming pursues a Cycle like this one:

Observation – Sensors record observational data from the crops, livestock, soil, or atmosphere.

Diagnostics – The sensor values are fed to a cloud-hosted IoT platform with predefined decision rules and models – also called “business logic” – that ascertain the condition of the examined object and identify any deficiencies or needs under IoT solutions.

Decisions – After issues are revealed, the IoT platform’s user and machine learning-driven ingredients decide whether location-specific treatment is compulsory and, if so, which.

Action – After end-user appraisal and step, the cycle repeats from the beginning under IoT solutions.