IoT in Agriculture and Farming

Article By : Vishal Goyal

IoT enabled agriculture can help to achieve the desired outcome and help to take informed decision. With the advent of ultra-low power and precision technologies it is now possible to connect every possible crop and livestock with IoT...

Agriculture is the primary source of food all over the world. It not only provides the food but raw materials for many industries and contribute significantly to the growth of GDP and economy of any country. It is also the main source of income in many countries.

With the evolution of urbanization, weather change and increasing population, agriculture sector is facing many challenges. There is a strong need to increase the production per unit area. Traditional method farming have led to degradation of farms because of uncontrolled use of resources, fertilizers and pesticides.

Smart agriculture has emerged as an important step towards increasing output and optimizing the use of resources. Smart agriculture is also very important towards organic farming and growing the type of fruits, vegetables or food grains demanded by consumers.

Smart farming is not only important for crops but also for livestock. Technology can help to increase the output of livestock, improve their health and avoid any outbreak or spread of diseases.

IoT in agriculture consists of sensors, processing, connectivity, gateway and cloud solutions optimized in their working according to specific use cases.

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Role of IoT in Agriculture Use Cases

Crop Monitoring

To get the maximum productivity of crops soil and the environment need to be monitored for humidity and temperature. It is important not only to monitor not only absolute humidity and temperature but the change over a shorter and longer period of time. This data can be correlated with ideal profile for the crop. This monitoring also helps to identify when and how much pesticides and fertilizer need to be used to minimize their usage.

Green House

As the demand of variety of fruits and vegetables is growing it becomes important to create ideal condition for a particular type of plant to grow and flourish. IoT enabled greenhouses monitor their ambient condition and adjust to avoid any deviation.

Remote Irrigation

Remote Irrigation is the next step of monitoring they control the irrigation depending upon the soil and ambient temperature and humidity. IoT enabled irrigation systems not only save water but also ensure that crops are provided with just the right quantity of water. In IoT enabled irrigation, the irrigation depends on the soil moisture rather than a prefixed or pre-determined interval based irrigation.

Livestock Monitoring

In IoT enabled farms, livestock such as sheep, pig, chicken and cows are monitored for their health to identify any disease, insemination period and activeness. IoT enabled sensors are fitted into ear or other parts of livestock body to monitor their body temperature and activeness. A livestock with abnormal temperature can be quarantined and provided medical care to avoid the outbreak of the disease to other livestock. The activeness in livestock is not only linked to health but also quality of the output. Milk production from active cow which is more than from an idle cow.

IoT enabled farms also monitor the ambience in which livestock are kept to ensure they are in proper living condition.

Geo Fencing

In large farms livestock are allowed to roam and live in natural condition. While they are not locked, it is important to ensure their safety and that they do not stray out of the farms. So they need to be monitored using GPS enabled tracker. The tracker consists of motion sensor to monitor their motion and GPS enabled geo fencing to generate alert if livestock moves out of designated area.

Architecture for IoT Enabled Smart Agriculture

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A typical IoT system in agriculture consists of following blocks

  • Sensors
  • Signal conditioning
  • Processing & Security
  • Power Management
  • Connectivity
  • Positioning

Sensors

Sensors are used to detect external inputs which act as a basis of any IoT system.

  • Accelerometers are used to detect motion, activity level, intrusion in the farm etc.
  • Humidity and Temperature sensors are used for soil monitoring, ambient Air monitoring and livestock health monitoring. These sensors provide critical input for IoT enablement in agriculture use cases.
  • Pressure sensor can detect atmospheric pressure that is eventually used to measure altitude as well. Since a pressure sensor requires an opening for a diaphragm to detect the pressure, they also prone to water and chemical contamination. Therefore, a pressure sensor is needed that can remain safe from chemicals such as Chlorine and Bromine.

Connectivity

Connectivity in agriculture may be viewed from below application requirements

  • Range:For indoor monitoring short range RF technologies such as Bluetooth, BLE and Wi-Fi are preferred as they can collect data from sensor nodes and send them to gateway for further propagation. For monitoring large farms long range technologies such as GPRS and LPWAN such as Sigfox are preferred as they give connectivity directly to telecom infrastructure. Mesh technologies such as BLE Mesh and 6LowPan can enhance the range of short range technologies and make them suitable to be used outdoor.
  • Power Consumption: Most of the use cases in agriculture are powered by non -rechargeable batteries so technologies such as BLE, RF subGhz and LPWAN such as Sigfox are preferred over Wi-Fi, Bluetooth and GPRS that consume exponentially higher power.

Therefore, we focus on BLE and subGhz in this article as they seem to be the most suitable connectivity technologies in agriculture ecosystem.

Bluetooth Low Energy [BLE] is a Wireless Personal Area Network [WLAN] technology and consumes a fraction of current of conventional Bluetooth and Wi-Fi while adding smartphone connectivity to devices. It works in 2.4Ghz frequency range, which is a worldwide license-free ISM band. BLE Mesh is a software solution for connecting multiple BLE devices in Mesh networks of IOT solutions. The introduction of the Mesh solution has made it possible to be connected even when devices are not in direct range of a network.

The BlueNRG-2 from STMicroelectronics is an ultralow-power BLE 5.0 certified system-on-chip, which provides seamless connection with sensors, privacy 1.2, secure connection 4.2, 8dbm of output power, and a reliable BLE link to IOT devices. Besides, it supports standard fully compliant SIG BLE Mesh.

Low-power Wide Area Network (LPWAN) technologies are another revolution in connectivity as they allow connectivity of several kilometers yet consume so little power that they can be powered by a non-rechargeable coin cell battery. Sigfox is a LPWAN technology which offers global cloud, long range connectivity, and consumes very low current.

To offer advantage of both short range and long range technologies in a combined solution, STMicroelectronics has introduced a unique solution to combine BLE and Sigfox radio, S2-LP, into a common solution. The dual radio offers long-range connectivity via Sigfox and Smartphone connectivity using BLE. Smartphone connectivity to Sigfox devices will enable User Interface [UI], over the Air firmware update [OTA], direct configuration and control.

Intelligence ont he Edge

One of the most important aspect of IoT in agriculture is to be able to analyze data of individual crops or livestock and relate them to actual productivity. Artificial Intelligence uses an assembly of nature-inspired computational methods, and machine learning refers to techniques that enable machines to recognize underlying patterns in order to make predictions and recommendations by analyzing data. But as the number of IoT enabled agriculture devices are numerous, the raw data sent from the sensors to the cloud sees the escalation in required data bandwidth and computational capabilities in the cloud.

Artificial Intelligence can be utilized efficiently when some of the analysis moves closer to sensing nodes or on the edge. Edge computing offers data privacy and reduced bandwidth requirements as well as cloud computation. Edge computing means intelligent sensing and processing at the node itself, so the selection of these devices is very important. A smart node analyzes the data, runs sensor algorithms, estimates the context, and sends the data to the cloud for further processing.

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Conclusion

As agriculture is the backbone of any society and burdened with ever increasing population it becomes imperative to maximize productivity and use the available resources optimally. IoT enabled agriculture can help to achieve the desired outcome and help to take informed decision. With the advent of ultra-low power and precision technologies it is now possible to connect every possible crop and livestock with IoT. A successful implementation requires working with right partners and leader in technology.

– Vishal Goyal, group manager, Technical Marketing South Asia and India, STMicroelectronics

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