Agricultural IoT

Introduction

• Currently, IoT-enabled technologies are widely used for increasing crop productivity, generating significant revenue, and efficient farming.
• The development of the IoT paradigm helps in precision farming. Agricultural loT systems perform crop health monitoring, water management, crop security, farming vehicle tracking, automatic seeding, and automatic pesticide spraying over the agricultural fields.
• In an IoT based agricultural system, different sensors necessarily have to be deployed over agricultural fields, and the sensed data from these sensors need to be transmitted to a centralized entity such as a server, cloud, or fog devices.
• Further, these data have to be processed and analyzed to provide various agricultural services. Finally, a user should be able to access these services from handheld devices or computers.

Basic Architecture Of An Agricultural IoT

Components of an Agricultural IoT

Cont…

• Cloud computing
• Sensors
• Cameras
• Satellites
• Analytics
• Wireless connectivity
• Handheld devices
• Drones

Use of IoT components in the agricultural chain

Advantages of IoT in Agriculture

• Automatic seeding: IoT-based agricultural systems are capable of autonomous seeding and planting over the agricultural fields. These systems significantly reduce manual effort, error probability, and delays in seeding and planting.
• Efficient fertilizer and pesticide distribution
• Water management
• Real-time and remote monitoring
• Easy yield estimation
• Production overview

Case Studies

• In-situ assessment of leaf area index using IoT-based agricultural system In this case study, we focus on an IoT-based agricultural system developed by Bauer et al. [1].
• The authors focus on the in-situ assessment of the leaf area index (LAI), which is considered as an essential parameter for the growth of most crops.
• LAI is a dimensionless quantity which indicates the total leaf area per unit ground area.
• For determining the canopy (the portion of the plant, which is above the ground) light, LAI plays an essential role.

Architecture

• The authors integrated the hardware and software components of their implementation in order to develop the IoT-based agricultural system for LAI assessment.
• One of the important components in this system is the wireless sensor network (WSN), which is used as the LAI assessment unit. The authors used two types of sensors:
• (i) ground-level sensor (G) and
• (ii) reference sensor (R).
• These sensors are used to measure photosynthetically active radiation (PAR). The distance between the two types of sensors must be optimal so that these are not located very far from one another. In this system, the above-ground sensor (R) acts as a cluster head while the other sensor nodes (Gs) are located below the canopy.

Cont…

• These Gs and R connect and form a star topology. A solar panel is used to charge the cluster head. The system is based on IoT architecture.
• Therefore, a cluster head is attached to a central base station, which acts as a gateway. Further, this gateway connects to an IoT infrastructure.

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Hardware

• For sensing and transmitting the data from the deployment fields to a centralized unit, such as a server and a cloud, different hardware components are used in the system.
• The commercial off-the-shelf (COTS) TelosB platform is used in the system.
• The TelosB motes are equipped with three types of sensors: temperature, humidity, and light sensors. With the help of an optical filter and diffuser accessory on the light sensors, the PAR is calculated to estimate the LAI. The system is based on the cluster concept.
• A Raspberry-Pi is used as a cluster head, which connects with four ground sensor motes. The Raspberry-Pi is a tiny single board, which works as a computer and is used to perform different operations in IoT.
• Humidity and wet plants intermittently cause attenuation to the system, which is minimized with the help of forward error coding (FEC) technique.

Cont…

• The real deployment of the LAI assessment system involves various environmental and wild-life challenges. Therefore, for reliable data delivery, the authors take the redundant approach of using both wired and wireless connectivity.
• In the first deployment generation, USB power supply is used to power-up the sensors motes.
• Additionally, the USB is used for configuring the sensor board and accessing the failure as per requirement. In this setup, a mechanical timer is used to switch off the sensor nodes during the night.
• In the second deployment generation, the cluster is formed with wireless connectivity. The ground sensor motes consist of external antennas, which help to communicate with the cluster head. A Raspberry-Pi with long-term evolution (LTE) is used as a gateway in this system.

Communication

• The LAI system consists of multiple components, such as WSN, IoT gateway, and IoT based network. All of these components are connected through wired or wireless links.
• The public land mobile network (PLMN) is used to establish connectivity between external IoT networks and the gateway. The data are analyzed and visualized with the help of a farm management information system (FMIS), which resides in the IoT-based infrastructure. Further, a prevalent data transport protocol: MQTT, is used in the system.
• We have already explored the details of MQTT in Chapter 8. MQTT is a very light-weight, publish/subscribe messaging protocol, which is widely used for different IoT applications.
• The wireless LAN is used for connecting the cluster head with a gateway. The TelosB motes are based on the IEEE 802.15.4 wireless protocol.

Software

• Software is an essential part of the system by which different operations of the system are executed. In order to operate the TelosB motes, TinyOS, an open-source, low-power operating system, is used.
• This OS is widely used for different WSN applications. Typically, in this system, the data acquired from the sensor node is stored with a timestamp and sequence number (SN).
• For wired deployments (the first generation deployment), the sampling rate used is 30 samples/hour. However, in the wireless deployment (the second generation), the sampling rate is significantly reduced to 6 samples/hour..

Cont…

• The TinyOS is capable of activating low-power listening modes of a mote, which is used for switching a mote into low-power mode during its idle state.
• In the ground sensor, TelosB motes broadcast the data frame, and the cluster head (Raspberry-Pi) receives it. This received data is transmitted to the gateway.
• Besides acquiring ground sensor data, the Raspberry-Pi works as a cluster head. In this system, the cluster head can re-boot any affected ground sensor node automatically.

IoT Architecture

• The MQTT broker runs in the Internet server of the system. This broker is responsible for receiving the data from the WSN. In the system, the graphical user interface (GUI) is built using an Apache server.
• The visualization of the data is performed at the server itself. Further, when a sensor fails, the server informs the users.
• The server can provide different system-related information to the smartphone of the registered user.

Smart Irrigation Management System

Cont…

• The primary objective of this system is to provide a Web-based platform to the farmer for managing the water supply of an irrigated agricultural field.
• The system is capable of providing a farmer-friendly interface by which the field condition can be monitored.
• With the help of this system, a farmer can take the necessary decision for the agricultural field based on the analysis of the data.
• However, the farmer need not worry about the complex background architecture of the system. It is an affordable solution for the farmers to access the agricultural field data easily and remotely.
• Architecture
• The architecture of this system consists of three layers: Sensing and actuating layer, remote processing and service layer, and application layer. These layers perform dedicated tasks depending on the requirements of the system.

Sensing and Actuating layer

• This layer deals with different physical devices, such as sensor nodes, actuators, and communication modules. In the system, a specially designated sensor node works as a cluster head to collect data from other sensor nodes, which are deployed on the field for sensing the value of soil moisture and water level. A cluster head is equipped with two communication module: ZigBee (IEEE 802.15.4) and General Packet Radio Service (GPRS).
• The communication between the deployed sensor nodes and the cluster head takes place with the help of ZigBee. Further, the cluster heads use GPRS to transmit data to the remote server.
• An electrically erasable programmable read-only memory (EEPROM), integrated with the cluster head, stores a predefined threshold value of water levels and soil moisture.

Cont…

• When the sensed value of the deployed sensor node drops below this predefined threshold value, a solenoid (pump) activates to start the irrigation process. In the system, the standard EC-05 soil moisture sensor is used along with the water level sensor, which is specifically designed and developed for this project.

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Processing and Service layer

• This layer acts as an intermediate layer between the sensing and actuating layer and the application layer. The sensed and process data is stored in the server for future use.
• Moreover, these data are accessible at any time from any remote location by authorized users. Depending on the sensed values from the deployed sensor nodes, the pump actuates to irrigate the field.

Application layer

• The farmer can access the status of the pump, whether it is in switch on/off, and the value of different soil parameters from his/her cell phone.
• This information is accessible with the help of the integrated GSM facility of the farmers’ cell phone. Additionally, an LED array indicator and LCD system is installed in the farmers’ house.
• Using the LCD and LED, a farmer can easily track the condition of his respective fields. Apart from this mechanism, a farmer can manually access field information with the help of a Web-based application.
• Moreover, the farmer can control the pump using his/her cell phone from a
• remote location.

Deployment

• The system has been deployed and experimented in two agricultural fields: (i) an agricultural field at the Indian Institute of Technology Kharagpur (IIT Kharagpur), India, and (ii) Benapur, a village near IIT Kharagpur, India. Both the agricultural fields were divided into 10 equal sub-fields of 3x3m2.
• In order to examine the performance, the system was deployed at over 4 sub-fields. Each of these sub-fields consists of a solenoid valve, a water level sensor, and a soil moisture sensor, along with a processing board.
• On the other hand, the remaining six sub-fields were irrigated through a manual conventional irrigation process.
• The comparison analysis between these six and four fields summarily reports that the designed system’s performance is superior to the conventional manual process of irrigation.