Wireless sensor networks (WSNs) can be used in agriculture to provide farmers with a large amount of information. Precision agriculture (PA) is a management strategy that employs information technology to improve quality and production. Utilizing wireless sensor technologies and management tools can lead to a highly effective, green agriculture. Based on PA management, the same routine to a crop regardless of site environments can be avoided. From several perspectives, field management can improve PA, including the provision of adequate nutrients for crops and the wastage of pesticides for the effective control of weeds, pests, and diseases. This review outlines the recent applications of WSNs in agriculture research as well as classifies and compares various wireless communication protocols, the taxonomy of energy-efficient and energy harvesting techniques for WSNs that can be used in agricultural monitoring systems, and comparison between early research works on agriculture-based WSNs. The challenges and limitations of WSNs in the agricultural domain are explored, and several power reduction and agricultural management techniques for long-term monitoring are highlighted. These approaches may also increase the number of opportunities for processing Internet of Things (IoT) data.

https://www.mdpi.com/1424-8220/17/8/1781/pdf

Energy-Efficient Wireless Sensor Networks for Precision Agriculture: A Review.

Wireless Sensing Technology is widely used everywhere in the current scientific world. As the technology is growing and changing rapidly, Wireless sensing Network (WSN) helps to upgrade the technology. In the research field of wireless sensor networks the power efficient time is a major issue. This problem can be overcome by using the ZigBee technology. The main idea of this is to understand how data travels through a wireless medium transmission using wireless sensor network and monitoring system. This paper design an irrigation system which is automated by using controllable parameter such as temperature, soil moisture and air humidity because they are the important factors to be controlled in PA(Precision Agricultures).

An automatic irrigation system using ZigBee in wireless sensor network

The Internet of Things (IoT) is converting the agriculture industry and solving the immense problems or the major challenges faced by the farmers todays in the field. India is one of the 13th countries in the world having scarcity of water resources. Due to ever increasing of world population, we are facing difficulties in the shortage of water resources, limited availability of land, difficult to manage the costs while meeting the demands of increasing consumption needs of a global population that is expected to grow by 70% by the year 2050. The influence of population growth on agriculture leads to a miserable impact on the farmers livelihood. To overcome the problems we design a low cost system for monitoring the agriculture farm which continuously measure the level of soil moisture of the plants and alert the farmers if the moisture content of particular plants is low via sms or an email. This system uses an esp8266 microcontroller and a moisture sensor using Losant platform. Losant is a simple and most powerful IoT cloud platform for the development of coming generation. It offers the real time data visualization of sensors data which can be operate from any part of the world irrespective of the position of field.

An IoT based soil moisture monitoring on Losant platform

Efficient and cost effective ways of irrigation have emerged as the need of the hour due to limited sweet water resources, especially the countries that are seriously hit by a lack of sweet water reservoirs. The majority of the water is wasted due to inefficient ways of watering plants. In this paper, we propose an intelligent approach for efficient plant irrigation that has a database of daily water needs of a type of plant and decides the amount of water for a plant type on the basis of the current moisture in soil, humidity, and time of the day. This approach not only saves sweet water by efficient utilization, but also supports smart consumption of energy. Our approach employs IoT and a set of sensors to efficiently record plant data and their watering needs and the approach is implemented with a mobile phone application interface that is used to continuously monitor and control the efficient watering system. The results of this study are easy to reproduce as the sensors used are cheap and easy to access. The study discusses in this paper is experimented on small area (such as tunnel farm) but the results of the experiments show that the used approach can be generalized and can be used for large size fields for efficient irrigation. The results of the experiments also outperform the manual approach and the similar approaches for sensor based irrigation systems.

https://www.mdpi.com/1996-1073/11/12/3427/pdf

Design and Implementation of an IoT System for Smart Energy Consumption and Smart Irrigation in Tunnel Farming

This paper presents an automation of farm irrigation system using a wireless sensor network (WSN) and embedded Linux board. The system provides a web interface to the user so that the user can control and monitor the system remotely. In this paper, Raspberry Pi is used as an embedded Linux board which is designed based on the arm 11 microcontroller architecture. Embedded Linux board makes the communication with all distributed sensor nodes placed in the farm through ZigBee protocol and itself act as a coordinated node in the wireless sensor network. The goal of coordinator node is to collect the parameters like soil moisture and soil temperature wirelessly. Each sensor node consists of soil moisture and soil temperature sensor and one ZigBee RF antenna device for communication with the coordinator node. Raspberry Pi stores collected data in the database and analyzes the stored data. The system will work according to the algorithm developed for watering the crop. The board has an Ethernet interface and runs the simple data web server. Hence coordinator collects the data over ZigBee wireless communication protocol and allow user to monitor the data from a web browser. User can make the irrigation system ON or OFF remotely. The system will reduce the water consumption and giving uniform water to the crop results in increasing yield.

Web based automatic irrigation system using wireless sensor network and embedded Linux board

The paper describes the automatic irrigation system using the Arduino microcontroller with grove moisture sensor and water flow sensor. The communication will be established using the Zigbee protocol and the control will be sent based on the moisture level of the soil using Arduino microcontroller. The two xbee radios's used in the network will be treated as master and slave in combination with the Arduino microcontroller. Here when a particular moisture level is reached, depending on the value of the moisture level water flow will be allowed in the pipe and the flow range, water pressure will be updated along with the time in a database and also displayed in the web portal. The owner of the agricultural field can anytime check the moisture level and the motor status. The motor's functionality status will also be a sent to the farmer's mobile using GSM.

Web based service to monitor automatic irrigation system for the agriculture field using sensors

Data analytics is playing a vital role in the modern industrial era. Electricity is one of the industries that have adapted data analytics techniques to a great extent. The data collected in the smart grid through smart meters and other sensors installed is very huge. The processing of such a huge heterogeneous data is not possible without the use of big data analytics technique. Big data analytics and machine learning algorithms play a vital role in electricity transmission and distribution network for data collection, storage and analysis of the data, prediction for data forecasting, and maintenance of the system. These techniques can help to optimally deliver energy at a lower cost with high quality and can also improve the customer service as well as social welfare. This article will review the use of big data analysis techniques along with the machine learning for various applications that can be mapped for smart grid environment. This article will also discuss the various methods and algorithm to be used for the applications for smart grid. A comparative analysis will also be done to show the best methods and algorithm to be used for a particular application.

The Role of Big Data Analytics in Smart Grid Management

Deep learning prospered as a distinct era of research and fragment of a wider family of machine learning, based on a set of algorithms that strengthen to model high-level abstractions in data. It tries to imitate the human intellect and learns from complicated input data and resolve different types of difficult and complex tasks. Because of Deep Learning, it was successful to deal with different input data types such as text, sound, and images in various fields. Improvement in deep-learning research has already influenced the search for speech recognition, automatic navigation systems, parallel computations, image processing, ImageNet, natural language processing, representation learning, Google translate, etc. Here, we present a review of DL and its applications including the recent development in natural language processing (NLP).

An Extensive Survey on Some Deep-Learning Applications

Summary In this paper we mainly focused on grayscale images and how these images can be decomposed into number of peaks. This decomposition is called the peak analysis of grayscale images. Due its sensitive definition, there is a wide range of applications for peak analysis. The detection criterion expresses the fact that important edges should not be missed. It is of paramount important to preserve, uncover or detect the geometric structure of image objects. Thus morphological filters, which are more suitable than linear filters for shape analysis, play a major role for geometry based enhancement and detection. A new method for image segmentation and tracking edges based on morphological transformation is proposed. This algorithm uses the morphological transformations dilation and erosion. A gradient determined grey level morphological procedure for edge increase and decrease is present. First, the maximum gradient, in the local neighborhood, forms the contribution to the erosion of the center pixel of that neighborhood. The gradients of the transformed image are then used as contributions to subsequent dilation of eroded image. The edge sharpening algorithm is applied on various sample images. Proposed algorithm segments the image by preserving important edges.

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Gray-level Morphological Operations for Image Segmentation and Tracking Edges on Medical Applications

This paper describes best fault tolerant topology design to develop the wireless sensor network efficiently. Here deploy the sensors on the agriculture field in the form of mesh topology because is the efficient and best one to form the wireless sensor network, which satisfies all the characteristics that depends to improve the efficiency and the quality of service. Implement a novel algorithm to detect the fault and how to recover the fault to reform the network without any distortion. In real time also we have create wireless sensor network. Here Mote is the combination of Arduino Microcontroller, Zigbee and the grove moisture sensor. They are placed in the agricultural field in the form of mesh topology is responsible to sense the moisture content available in the soil. Here use the Connected Dominating Set (CDS) algorithm to find out the sink node from the set of nodes based on the mesh topology to increase the efficiency. Real time deployment of sensors on the sensor field and make a communication using the zigbee. Based on the novel algorithm to increase the efficiency to recover the network from the faults when the number of nodes increases.

M. Usha Rani

Papers

Web based service to monitor automatic irrigation system for the agriculture field using sensors

The Role of Big Data Analytics in Smart Grid Management

An Extensive Survey on Some Deep-Learning Applications

Gray-level Morphological Operations for Image Segmentation and Tracking Edges on Medical Applications

Energy efficient fault tolerant topology scheme for precision agriculture using wireless sensor network