Agricultural Internet of Things technology applications

Technological development follows no physical or invisible boundaries and expands its roots in all directions. Likewise, the Internet of Things has its applications in fields of home security, Industry (as Industrial Internet of Things) and smart cities. But technological development within the Internet of Things has even sown its seeds in the agricultural sector, leading to the Agricultural Internet of Things.

Figure 1: Agriculture Internet of Things near future.

Agriculture Internet of Things in the near future

Agricultural IoT future (2050) and market size

It is forecasted that by the year 2050, the Agricultural Internet of Things will increase food production by 70% and be feeding up to 9.6 billion people.

Therese Cory, Beecham Research analyst and author of Towards Smart Farming, stated: “The demand for more food has to be set against the challenges of rising climate change and more extreme weather conditions, along with the environmental impact resulting from intensive farming practices.”

Global shift timeline

Considering the growth of IoT since 2000, the use of sensors presents a major shift in agriculture.

  • Year 2000 Globally, there were 525 million farms on record, out of which not a single farm was connected to the Internet of Things.
  • Year 2025 With same base of 525 million farms, there will be 600 million sensors in use at these farms – representing a major shift towards technological advancements being applied to agriculture to support the Agricultural Internet of Things.
  • Year 2035 With 525 million farms globally, there will be a more than threefold growth in sensor usage compared to the year 2020. By 2050, there will be two billion sensors used in 525 million farms.
Image 1: Electronic agricultural devices

Electronic agricultural devices

Product quality, higher crop productivity, resource conservation and cost control – these are just a few of the ways the Agricultural Internet of Things promises to transform farming and food production in the future. It helps increase crop productivity by managing and controlling such activities in the following ways:

Water supply management

Purportedly, it has the potential to conserve 50 billion gallons of fresh water in a year. Adequate water supply is essential for agriculture; crops can be damaged by either water excess or shortage. The Agricultural IoT, integrated with Web Map Service (WMS) and Sensor Observation Service (SOS) provides a solution to managing water requirements or supply for crop irrigation. It also smartly analyzes crop water requirements and uses water supply resources available to reduce waste.

In areas of drought, the crop water management function of Agricultural IoT can be of great value, as it intelligently manages the limited water supply by calculating the valve operation timing and building optimum irrigation strategy, resulting in better practices to preserve water resources.

Precision agriculture

Weather forecasting accuracy and other dynamic data inputs can affects crop productivity to a great extent. The higher the level of accuracy, the lower the chances of crops being damaged; thus, more accurate weather forecasts can lead to higher profitability and productivity levels.

It ensures accurate and efficient communication to farmers of real time data related to dynamic agricultural processes (like weather forecasts, planting, harvesting, etc.), weather forecasts, soil quality, and availability and cost of labor. Farmers who have access to such important real-time information available to them can better plan their course of activities beforehand and take corrective or preventive measures in advance for the future.

Integrated Pest Management or Control (IPM/C) 

A farmers’ hard work is often destroyed by pests, causing significant monetary losses. To prevent such situations, the Agricultural IoT (Internet of Things) has a system to monitor and scan the environmental parameters and plant growth. There is also data available from pest control sensors which are capable of predicting pest behavior. This information can be used by farmers to reduce damage done by pests on a large scale. Pest Management and Control works on the following fundamental bases:

  • Observation
  • Inspection
  • Identification
  • Record Tracking

Food production and safety

Along with attaining optimum, quality food production, the Agricultural IoT aims to ensure food safety at different levels, like storage, transportation, etc. To do so, it has a monitoring system over various factors like shipping time, storage temperature, and cloud-based record keeping.

Livestock management

Supporting livestock health fortified with monitoring tools like as ear tags for cattle, capable of detecting respiratory diseases. If a disease is detected, it sends an alert so the animal can be separated from the herd, preventing the disease from spreading.

Examples of new applications

  1. The Phenonet Project by Open IoT  The Phenonet enables plant breeders to evaluate the performance of differentiated wheat varieties with the help of measurements taken from remote sensors. These sensors are capable of monitoring various factors like soil temperature, humidity, air temperature, etc.
    • This helps to improve quality and helps the plant breeders to monitor and promote plant growth under various climate conditions.
    • The Phenonet Project is a step ahead in the Agricultural IoT, driving improved quality by measuring on field environmental and plant physiology parameters resulting in improved quality.

2. CLAAS Equipment  CLASS is a leading manufacturer of agricultural machinery founded in 1913. The CLASS Agriculture Internet of Things equipment can be operated on autopilot and farmers can receive advice on ways to improve crop productivity and reduce grain losses.

CLAAS agricultural equipment

CLAAS agricultural equipment

  • CLASS has entered a partnership venture with 365FarmNet to facilitate the service to farmers, in which they can manage and control their agricultural plotting via a computer or smartphone;
  • It collects important pieces of information for further analysis. This information may be used in field mapping and in various planning programs like fertilization and nutrient planning.

3. Precisionhawk’s UAV Sensor platform Unmanned Aerial Vehicle (UAV) Sensors efficiently collect superior quality data, then analyze it to give farmers relevant information like wind speed, air pressure, etc. This platform can also be used in civil services like surveying, mapping and imaging of agricultural plots.

Unmanned Aerial Vehicle (UAV)

Unmanned Aerial Vehicle (UAV)

  • Precisionhawk UAV uses a drone to carry out its operational data collection and monitoring. It is the farmer who guides the drone over the fields to be surveyed, while also deciding from what altitude.

4. Cleangrow’s Carbon Nanotube Probe – CleanGrow Ltd., founded 2009, and facilitates making quick measurements of ion concentrations in a given liquid. In other words, the firm measures the various nutrient levels present in a given liquid on a field.

  • Cleangrow Ltd. uses the Carbon Nanotube Probe as a transducing layer in the sensors, enabling the measurement or test for multiple ions in a solo device. This meter provides instant feedback to the user.
Temputech’s Wireless Sensor Monitoring

Temputech’s Wireless Sensor Monitoring

  • In addition, farmers can set alarms for various factors or situations related to temperature, humidity and vibration.

Venture investment

From 2014 until recently, there was a total venture capital investment of $269 million in more than 40 different deals in agriculture and food startups, with some of the leading IT giants investing as much as $15 Billion in Farmers Business Network.

Learn more

  • To learn more about how IBM Watson IoT can help you obtain greater efficiency through smarter asset management, please read our white paper, Understanding the Value of Enterprise Asset Management or contact a representative today.
  • To find out more about the work IBM is doing to improve agricultural process, read our research here.
  • This article originally appeared on IoT Worm.

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