Smart and Precise Farming Using IoT in Agriculture!

IoT in Agriculture can be considered as Digitalization of Agriculture in terms of the utilization of internet technology and smart agriculture sensors in farming processes. Deployment of Advanced farming technology would increase the efficiency and effectiveness of farming practices and hence fetch sustainability to the farmers.

Higher efficiency can be realized in higher productivity with lesser resources employed (more production with the same resources OR same production with lesser resources) and minimized wastages during various Agricultural processes/stages. Effectiveness in farming can be enhanced by the connectivity and resourcefulness of the farmers to take the right actions timely to mitigate the farming risks and maximize the yields and monetary returns.

Generally, farming has the following Sub-functions/Sub-processes/stages in crop lifecycle:

  1. Crop planning – Decisions pertaining to crop identification and growing during the harvesting cycle. This would also include the seed selection, quantity required, preparation of seed for sowing, etc. type and condition of the land, and land fertility…
  2. Land Preparation – Activities related to Clearing and Weeding the field, Pre-irrigation, first Plowing or tilling, Harrowing, Flooding, Levelling
  3. Seed Sowing:  Field practices including traditional methods, Broadcasting, Dibbling, Drilling, Seed Dropping, Transplanting, Hill Dropping, Check Row Planting
  4. Soil Nutrition: Assessment of need (type, concentrations, productivity, fertility) of Natural and Chemical nutrients/fertilizers, their storage, preparation, and application manually or with machines
  5. Irrigation: performing irrigation of crops through Sprinkler irrigation, surface irrigation, drip irrigation, sub-irrigation, and/or manual irrigation.
  6. Crop Protection: Pre-harvest weeding through Biological, Physical, Chemical, Mechanical, and cultural practices/methods
  7. Harvesting – Reaping, threshing, cleaning, and hauling using labor and machines
  8. Storage: Post-harvest storage of crops in bags or metal containers

The field productivity and crop quality can be improved substantially if the farmers can optimize the resources during each of the above-stated stages. 

As the farmers are veterans in the farming process they know the desired measures to take against any situation, however, precise site intelligence pertaining to soil moisture & pH; farm equipment allocations; crop growth; the presence of weeds, diseases, and pests; fertilizer and pesticides application and weather condition including temperature, humidity, rain, etc. can greatly enhance the situational awareness of the farmers and hence the corresponding responses from them, leading to better crop management and increased field productivity.

Segmentation of the Internet of Things (IoT) in Agriculture

A) Supply-side IoT Value add in Digital Farming

  • Technology Developers
    • Hardware: computing, networking, internet, IoT agriculture sensors
    • Software : PaaS, IaaS, SaaS
  • System Integrators
  • Product Resellers
  • Process Consultant

B) Demand-side Value Add of IoT in Agriculture Systems

  • Crop Planning: information on weather, Soil, Irrigation, Mandi, transportation, Bank loan, etc.
  • Land Preparation:  resource allocation, Soil fertility, pH, Moisture assessment
  • Seed Sowing: Seed Lifecycle,
  • Soil Nutrition: NPK monitoring, recommendation on soil fertility, fertilizer cost
  • Irrigation: Moisture and Humidity monitoring and Management, rain forecasting, irrigation expense reporting
  • Crop Protection: Weeds and pests identification, pesticide spray using Drone, pesticides -cost reporting
  • Harvesting: Produce forecasting, labor assessment, Harvesting-expense reporting
  • Storage: condition monitoring and Management, transportation and storage-expense reporting, Mandi/FCI/Mill delivery reporting

Applications of IoT in Agriculture: Digital Agriculture

If you relook at the above section, you may observe that Precision Farming offers resource optimization opportunities and bridges the gap between the ideal resource requirement (time, quantity, quality) of the field & crop and the actual resources deployed by the farmers. In addition, it adds value regarding the situational awareness of the farmers which will impact their decision-making capability…

The Internet of Things (IoT) is an enabler of the required precision in agriculture for farmers by providing accurate and real-time information on the site using an integrated network of various sensors, gateways, the internet, cloud applications, smartphones, and apps.

Based on the subject expertise and available resources different companies and start-ups are offering niche-based solutions, targeting one or more value-adding instances in the agriculture and crop lifecycle. For example, GSM internet-based IoT pump controllers are helping the farmers remotely manage the pump operations and efficiently meet the irrigation requirements of the fields. Thus saving unnecessary manual labor employed merely to operate the pumps. Also, it helps to avoid over usage of pumps to save water and power…

Based on the above foreground, we can consider the following broad application of the Internet of Things in the agriculture sector:

Crop Monitoring and Management

IoT technology has revolutionized the way crops are monitored and managed. With sensors and other IoT devices, farmers can monitor soil moisture levels, temperature, humidity, and other environmental factors that can affect crop growth. By collecting and analyzing data, farmers can make informed decisions about when to plant, water, and harvest their crops. This can lead to improved crop yields and reduced water usage.

One of the most popular IoT applications in crop monitoring and management is precision agriculture. This approach involves using IoT devices to collect data about crop health, soil conditions, and weather patterns. The data is then analyzed to identify areas that require attention, such as areas with low soil moisture levels or pests. This information is then used to optimize crop management practices, such as irrigation and fertilizer application, to improve crop yields.

Smart Irrigation

Smart irrigation is another IoT application in agriculture that has gained popularity in recent years. With traditional irrigation systems, water is often wasted due to overwatering or inefficient distribution. IoT technology can help farmers optimize water usage by providing real-time data on soil moisture levels and weather conditions. This data can be used to adjust irrigation schedules and optimize water usage, resulting in water savings and improved crop yields. IoT-enabled irrigation systems can also ensure that water is delivered precisely where it is needed, reducing water loss due to runoff or evaporation.

One example of smart irrigation in agriculture is the use of soil moisture sensors. These sensors can be placed throughout the field to measure soil moisture levels at different depths. The data is then transmitted to a central system that analyzes the data and provides recommendations for irrigation scheduling. This can help farmers save water and reduce irrigation costs, while also improving crop yields.

Automated Farming

IoT technology can also be used to automate various farming processes, such as planting, harvesting, and fertilizing. With IoT devices, farmers can remotely monitor and control farming equipment, reducing labor costs and increasing efficiency. This can help farmers save time and money, while also improving crop yields.

One example of automated farming in agriculture is the use of drones. Drones can be equipped with sensors and cameras to collect data on crop health, soil moisture levels, and other environmental factors. This data can be used to create detailed maps of the field, which can then be used to automate planting, fertilizing, and harvesting processes. This can lead to improved crop yields and reduced labor costs.

Data Analytics

IoT technology generates vast amounts of data that can be used to optimize farming practices and improve crop yields. With data analytics tools, farmers can analyze this data to identify patterns and make informed decisions about farming practices. This can lead to improved efficiency, reduced costs, and increased productivity.

One example of data analytics in agriculture is the use of predictive analytics. Predictive analytics involves using historical data and statistical algorithms to predict future outcomes. Additionally, real-time data on weather conditions, soil moisture, and other factors can be used to create predictive models for crop growth and yield. This approach allows farmers to anticipate potential problems and make informed decisions about planting, harvesting, and other critical activities.

Pest Management

IoT technology can also be used to improve pest management. Sensors can detect the presence of pests and alert farmers to potential infestations. IoT-enabled pest control systems can also be used to release beneficial insects or apply pesticides precisely where they are needed, reducing the use of chemicals and minimizing harm to the environment.

Supply Chain Management

IoT technology can be used to improve the efficiency of the agricultural supply chain. Sensors can track the location and condition of crops and livestock during transportation. This data can help farmers and food processors reduce waste, ensure quality, and meet regulatory requirements. IoT-enabled tracking systems can also help prevent food fraud by ensuring the authenticity of products.

Livestock Management

IoT technology can also be used to improve livestock management practices. With IoT devices, farmers can monitor the health and behavior of their livestock, track their movements, activity levels, temperature, and other vital signs; and even automate feeding and milking processes. This data can help farmers identify when an animal is sick or injured, allowing for early intervention and treatment. This can lead to improved animal welfare, reduced labor costs, and increased productivity.

One example of IoT in livestock management is the use of RFID tags to track the movement of animals. These tags can be placed on animals and used to track their location, behavior, and health status. The data is then analyzed to identify potential health issues or behavioral patterns that require attention. This can help farmers identify and address health issues early, leading to improved animal welfare and increased productivity.

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