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Agricultural Development and “Smart Farming”

   In pursuit of improved agricultural production, TerraVerde Agriculture offers “Smart Farming” technologies amongst the solutions it offers.

What is special about “Smart Farming”? and what benefits does it provide?

The “Smart Farming” space, also known and referred to by some as “Precision Farming” is support of agricultural production decisions in an accurate and appropriate manner by utilizing novel technologies in the fields of sensing, Internet of Things (IoT), big data collection and acquisition, sophisticated data analysis and feedback to the farm and farmer.

Smart Farming is based on knowledge and the objective is to increase production levels by being precise in implementing that knowledge, while saving on inputs and costs. In other words, Smart Farming comes to make production more efficient physically and economically.

The advent of Smart Farming is a direct consequence of the development of information and communications technologies during the recent decades.

The development of these technologies is based on the belief that higher efficiencies can be achieved by utilizing information and communications technology (ICT), the “Internet of Things” and the ability to access and crunch vast amounts of data and return clear , meaningful, and actionable items to the farm and farmer.

Smart Farming Components

Generally, technology utilized for farm management intervention in Smart Farming can be divided according to  The type of sensors and sensing methods used in the field and the datasets utilized and quality of data analysis.

Sensing

Precision sensing
Sensing can be localized, intensive and continuous, which is achieved with precision devices:

  • Plant devices attached or in very close proximity to plants continuously measuring plant growth, temperature, shade, color patterns, pests and pest damage, fruit size, etc.
  • Soil sensitive devices measuring soil moisture, temperature, salinity, pH, oxygen, etc. 
  • Devices that measure numerous meteorological parameters.
  • Precision sensing in real-time, provides continuous localized information with high precision.
Remote sensing
Alternatively, sensing can be remote which is achieved with cameras or similar devices mounted on poles, drones, aircraft, or satellites.
The character, resolution and value of the captured images vary according to technology, distance, wavelength, and other factors, and usually represent the status of whole fields or plots in contrast to precision sensing that continuously gauges individual plants. This means that remote sensing captures a whole field status and the variation it reflects.

Data and data analysis

Datasets
Providers of Smart Farming solutions differ in the type, number, and detail level of datasets they utilize.
Data can be obtained from the deployed sensors or external providers of data – proprietary, from growers, or from the public domain.

Data Analysis
The ability to derive insights from the datasets and provide quality information and directives to growers is determined by the depth of data analysis utilized by the supplier and is key to the quality of the supplier. Most providers claim to utilize Artificial Intelligence (AI), Machine Learning as well as Deep Learning in the algorithms they develop.
Suppliers differ substantially in the level and quality of data analysis outputs they provide, particularly when undertaking to provide actionable information to growers.
Whatever the case Smart Farming is perceived as a beneficial approach to streamlining agricultural production and it is presently on the sharp growth curve of its lifecycle.

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