Wireless Sensor Networks for Agricultural IoT

Sensor Networks, Sensor-cloud Framework and Edge-based Compuation for Internet of Things in Agriculture

In the Indian scenario, the Wireless Sensor Network (WSN)-based farming solutions need to be of very low cost to be affordable by end users. Physical phenomena such as temperature, humidity, and rainfall over an agricultural region can be monitored by a WSN. WSNs for environmental condition monitoring with information of soil nutrients is a promising approach for predicting crop health and production quality over time. Monitoring the soil moisture and weather conditions enables irrigation scheduling. Agricultural IoT involving huge number of sensor nodes, spread all over the agrarian area, and generating large volumes of data requires cloud-framework and edge-level computation.

We propose, design and deploy several architectures for implementing agricultural IoT and study the impact of intensive processing tasks on the network parameters. Additionally, we surveyed WSN deployments for various farming applications in the Indian as well as global scenario. We highlight the prospects and problems in this regard, while identifying the factors for improvement and future directions of work using the new age technologies.

 

Agricultural IoT Deployments

In this work, we propose a hardware prototype using Wireless Sensor Network (WSN) for intruder detection in an agricultural field. The proposed system is named Agricultural Intrusion Detection (AID). AID helps to generate alarms in the farmer’s house and at the same time transmits a text message to the farmer’s cell phone when an intruder enters into the field.

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In this paper, we study the problem of integration and configuration of a peripheral with a processor is practically a big challenge to enable PnP in the IoT device. Available heterogeneous sensors are mainly compatible with the embedded interfacing protocols such as SPI, I2C, UART, ADC, and Digital. To solve this problem, we present an architecture of a plug-and-play (PnP)-enabled IoT device, which supports heterogeneous embedded peripheral communication protocols. We propose the architecture of SensPnP, divided into two parts — a) Universal plug-and-play (UniPnP) controller and b) Plug-and-play (PnP) peripheral module as shown in the figure above.

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In this paper, we propose to dismiss the requirement of certain seemingly crucial identifier fields from packets arriving through various sensor nodes in an agricultural IoT deployment. The proposed approach reduces packet size, thereby reducing channel traffic and energy consumption, as well as retaining the capability of identifying these originating nodes. We propose a method of a blind agricultural IoT node and sensor identification, which can be sourced and operated from a master node as well as a remote server.

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In this paper, we present the design of an IoT-based dynamic irrigation scheduling system (AgriSens for efficient water management of irrigated crop fields. The AgriSens has a farmer-friendly user interface , which provides field information to the farmers in a multi-modal manner — visual display, cell phone, and Web portal. It achieves significant results with respect to different performance metrics such as data validation, packet delivery ratio, energy consumption, and failure rate in various climatic conditions and with dynamic irrigation treatments.

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Sensor-cloud Framework for Agricultural IoT

In this paper, we highlight the benefits of using sensor-cloud framework for the efficient addressing of various agricultural problems. We address the specific challenges associated with designing a sensor-cloud system for agricultural applications. We also mathematically characterize the virtualization technique underlying the proposed sensor-cloud framework by considering the specific challenges. Furthermore, the energy optimization framework and duty scheduling to conserve energy in the sensor-cloud framework is presented.

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Intra-Edge Processing in Agricultural IoT

In this work, we address the challenges of a decentralized and heterogeneous Unmanned Aerial Vehicle (UAV) swarm deployment – some fitted with multimedia sensors, while others armed with scalar sensors – in resource-constrained and challenging environments, typically associated with farming. We also address the resulting problem of sensing and processing resource-intensive data aerially within the Edge swarm in the fastest and most efficient manner possible. To address this, we propose a Nash bargaining-based weighted intra-Edge processing offload scheme to mitigate the problem of heavy processing in some of the swarm members.

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In this work, we address the problem of constrained processing capabilities of the in-field nodes and the network throughput. We propose and evaluate a low-latency method of increasing the packet throughput in agricultural IoT implementations. The proposed method envisions removal of node identifiers from packets before transmission and predictive packet-source mapping method within the edge layer of an agrarian Internet of Things (IoT) implementation.

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Wireless Sensor Networks for Agriculture: A Survey

In this paper, we review the potential WSN applications, and the specific issues and challenges associated with deploying WSNs for improved farming. To focus on the specific requirements, the devices, sensors and communication techniques associated with WSNs in agricultural applications are analyzed comprehensively. In this regard, the WSN deployments for various farming applications in the Indian as well as global scenario are surveyed. We highlight the prospects and problems of these solutions, while identifying the factors for improvement and future directions of work using the new age technologies.

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Internet of Things for Agriculture: The State of The Art

In this paper, we investigate the specific issues and challenges associated with IoT, and review various IoT architectures, communication, middleware, and information processing technologies. We, then, discuss few IoT applications for agriculture – presenting various case studies to thoroughly analyze the solutions along with their design and implementation related parameters. Consequently, we provide a comprehensive review of the available simulation tools, datasets, and testbeds which provisions experimentation with IoT in agriculture.

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