Study of Wireless Sensor Network Applications in Network Optimization

Because of the rapid development of wireless sensor network, it widely applied in all areas of life, in-depth study of the technology will also explore the potential application of more in-depth. The main research of WSN technology in some environment in the real world information acquisition and processing technology, it realizes the intercommunication of the real world and the Internet world, opened the human WSN network era. WSN network through the digital world com. Human concepts inherent information world and explore the objective facts, from the inquiry from change the people and things in nature, the data are the basic objects interactively; the sensor node has sensing effect in direct contact with the objective environment, continuously enhance the practical function of virtual networks, but also increase the capacity of human understanding of the objective world; through the real-time sensing and found the state change monitoring target, at the same time the collection of data processing, the processing of useful information through the wireless transmission mode is transmitted to a data collection center or client. It will make the development and wide application in various fields of social life are more intelligent and modernization. Although its development still in an immature stage, Tan of many problems still has not obtained the very good solution, research work on WSN is far from over. In this paper the concept and system structure of wireless sensor network analysis began to design, application system based on wireless sensor network monitoring farmland use temperature and humidity ZigBee as an example to study the development process of application system for wireless sensor networks

Survey of Impact of Technology on Effective Implementation of Precision Farming in India

The advancements in technology have made its impact on almost every field. India being an agricultural country, proper use of technology can greatly help in improving the standard of living of the farmers. With varying weather conditions, illiteracy of farmers and non-availability of timely assistance, the farmers of this country could not get the best out of their efforts. Precision farming focuses mainly on the aspects that can improve the efficiency based on the data collected from various sources viz. meteorology, sensors, GIS, GPS, etc. The information pertaining to farmland (e.g., soil moisture, soil pH, soil nitrogen) and agro-meteorology (e.g., temperature & humidity, solar radiation, wind speed, atmospheric CO2 concentration, rainfall, climate change and global warming) are used as input parameters to decide the varying requirements of the crop cultivation. Historical farm land data are used as a means to decide on the kind of actions to be taken under a specific scenario. This paper surveys the existing methods of precision farming and highlights the impact of technology in farming. An overview of different technologies used in precision farming around the world and their implications on the yield are discussed. The methods adopted towards managing different types of crops, the varying environmental conditions and the use of realtime data being collected through sensors are also analyzed. Also, the need for dynamic approaches to assist the farmers in taking context specific decisions has been highlighted

Coverage and density of a low power, low data rate, spread spectrum wireless sensor network for agricultural monitoring

A physical layer specification for a low power, low complexity, low data rate sensor network suitable for agricultural monitoring is investigated. Code division multiple access (CDMA) with high processing gain is used to facilitate transmission powers which comply with the Ultra Wide Band (UWB) spectral mask, and this permits physically small nodes with limited energy storage capacity. The interference arising from each node is calculated, and it is shown that for the investigated scenario and specification, an aggregate data rate of 2 bytes per minute and a node population of approximately 1000 can be supported at distances up to a few kilometres from the central node, with less than 0.2% chance of failure due to multiple access interference

A Data Collecting Strategy for Farmland WSNs using a Mobile Sink

To the characteristics of large number of sensor nodes, wide area and unbalanced energy consumption in farmland Wireless Sensor Networks, an efficient data collection strategy (GCMS) based on grid clustering and a mobile sink is proposed. Firstly, cluster is divided based on virtual grid, and the cluster head is selected by considering node position and residual energy. Then, an optimal mobile path and residence time allocation mechanism for mobile sink are proposed. Finally, GCMS is simulated and compared with LEACH and GRDG. Simulation results show that GCMS can significantly prolong the network lifetime and increase the amount of data collection, especially suitable for large-scale farmland Wireless Sensor Networks

Review—Machine Learning Techniques in Wireless Sensor Network Based Precision Agriculture

The use of sensors and the Internet of Things (IoT) is key to moving the world\u27s agriculture to a more productive and sustainable path. Recent advancements in IoT, Wireless Sensor Networks (WSN), and Information and Communication Technology (ICT) have the potential to address some of the environmental, economic, and technical challenges as well as opportunities in this sector. As the number of interconnected devices continues to grow, this generates more big data with multiple modalities and spatial and temporal variations. Intelligent processing and analysis of this big data are necessary to developing a higher level of knowledge base and insights that results in better decision making, forecasting, and reliable management of sensors. This paper is a comprehensive review of the application of different machine learning algorithms in sensor data analytics within the agricultural ecosystem. It further discusses a case study on an IoT based data-driven smart farm prototype as an integrated food, energy, and water (FEW) system

Solar Powered WSN for monitoring environment and soil parameters by specific app for mobile devices usable for early flood prediction or water savings

This paper describes the design and realization of a smart electronic system, based on a Wireless Sensor Network, for wide-area monitoring of availability level and rapid changes of the water presence in the monitored soil in order to guarantee flood prediction, water savings in the optimized farmland irrigation, waste reduction and optimal use of water resources where its availability is low. The designed sensor node, by means of the different embedded sensors, is capable of detecting environmental parameters, the solar radiation level and soil temperature and moisture (i.e. water volume content) values. The sensors communicate with a central processing unit located on board, used both as data processing unit and as Wi-Fi transceiver to receive/transmit the sensors data. The user near a sensor node, by a tablet or smartphone with an appropriate app, can collect information provided from sensors and share them with all users who use the same app on the Cloud, through peer to peer Wi-Fi or other internet connection

Root Zone Sensors for Irrigation Management in Intensive Agriculture

Crop irrigation uses more than 70% of the world’s water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower’s experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS’ (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy

Exploring Wireless Sensor Network Technology In Sustainable Okra Garden: A Comparative Analysis Of Okra Grown In Different Fertilizer Treatments

The goal of this project was to explore commercial agricultural and irrigation sensor kits and to discern if the commercial wireless sensor network (WSN) is a viable tool for providing accurate real-time farm data at the nexus of food energy and water. The smart garden consists of two different varieties of Abelmoschus esculentus (okra) planted in raised beds, each grown under two different fertilizer treatments. Soil watermark sensors were programed to evaluate soil moisture and dictate irrigation events up to four times a day, while soil temperature and photosynthetic solar radiation sensors also recorded data every six hours. Solar panels harvested energy to power water pump and sensors. The objectives of the experiments were to evaluate and compare plant and soil parameters of the two okra varieties grown under two different fertilizer treatments. The plant parameters evaluated and compared were basal diameter, plant height, fruit production, and fruit size. Soil parameters measured were soil moisture, soil temperature, and soil nitrate concentration. The commercial sensors were evaluated on efficiency, accuracy, ease of use and overall practicality. Clemson spineless produced larger okra plants with the highest plant parameter values, followed by Emerald okra. However, they both averaged nearly the same yield and length of okra fruit. Nature’s Care fertilizer leached more in beds containing Clemson spineless, while Garden-tone leached more in beds containing Emerald okra. When the WSN is installed properly, the system’s great performance undoubtedly aides the farmer by providing real time field data. However, a properly installed apparatus does not promise a stable system. There are numerous challenges and limitations of which can diminish the performance quality of the WSN, those being battery power, data transmission, and data storage. Data storage is also an issue depending on the amount of data collected, rate of data collection, and size of storage unit. These issues can hinder the decision making for precision farmers

Precision Agriculture Technology for Crop Farming

This book provides a review of precision agriculture technology development, followed by a presentation of the state-of-the-art and future requirements of precision agriculture technology. It presents different styles of precision agriculture technologies suitable for large scale mechanized farming; highly automated community-based mechanized production; and fully mechanized farming practices commonly seen in emerging economic regions. The book emphasizes the introduction of core technical features of sensing, data processing and interpretation technologies, crop modeling and production control theory, intelligent machinery and field robots for precision agriculture production