Smart Technologies with Wireless Sensor Networks

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

Wireless sensor node is an autonomous and compact device that has capability to monitor a variety of real-world phenomena. It is designed composed of sensing device, embedded processor, communication module, and power equipment. Wireless sensor node is part of wireless sensor network where hundred or thousand sensor node can be deployed. Over the past decade Wireless Sensor Networks (WSNs) have emerged as one of the computing platforms of note within the electronics community. In prediction, there will be more than 127 million wireless sensor nodes deployed worldwide by 2014. We have surveyed 100 currently available wireless sensor network node platforms have been developed and produced not only by the research institutions, the universities but also some companies in last ten years. In this paper, we present a review of 27 different wireless sensor node platforms. We review these devices under a number of different parameters, and we highlight the key advantages of each node platform according to dimension and power consumption. We also discuss the characteristics and trend of development and deployment a wireless sensor node technology.

With the advent of technology MEMS came surpassing and led to the design of very small sensor nodes. This led to the creation of wireless sensor nodes. Background: Wireless Sensor Networks are entrancing to researchers due to their wide range of ever-growing application potential in every area and have been adapted in order to implement many applications such as habitat monitoring, military surveillance, precision agriculture. One of the major design challenges in Wireless Sensor Networks is power consumption. Analysis: It is crucial in various functions to position sensor nodes in an efficient way in order to monitor the event squarely and deliver the data to sink node. Uneven power consumption by nodes leads to the creation of energy holes, which means that data can never be delivered to the sink on that path. Findings: The sensor nodes located near to the sink node as the precedence, as there are the first ones to get effected due to this power consumption patterns and in 99 percent of the cases the first and the second rings are the places where an energy hole is first created. The main aim of this paper is to develop an algorithm using hashing technique which reduces the power consumption and energy harvesting is done optimally by avoiding duplication of packets in static network. Improvements: The power consumption improvement ratio and the life elongation of the network were simulated using Network simulator tool using the hashing technique and avoiding duplication of packets.

While wireless sensor networks are finding an ever increasing number of applications in many areas, they still lack the most powerful human sense - vision. This is largely due to the problems associated with processing and communicating the large volume of image data over energy constrained sensor nodes. Available wireless sensor nodes are severely constrained in both processing capability and energy. This paper presents an innovative architecture and protocol for energy efficient processing and communication of images over wireless sensor networks. The proposed hardware architecture is optimized to achieve high speed image compression with minimum hardware requirement and low power consumption. An efficient and reliable transmission protocol for compressed image is also presented. It incorporates an effective image packet queue control strategy to reduce packet error rate and increase image transmission throughput. Experimental results demonstrate the effectiveness of these novel approaches to make image compression and communication over wireless sensor networks feasible, reliable and efficient.

One important issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is a scarce resource in a sensor node. Many protocols have been proposed for data-gathering between wireless sensor nodes. However, most of these protocols work on static wireless sensor networks. In this paper, we provide clustering-based and time-driven protocols which minimize energy dissipation for data-gathering in wireless mobile sensor networks where the sensor nodes are capable of mobility. We first consider the node mobility when organizing clusters. Our protocols will have a sensor node select a proper cluster-head to join in order to save energy. We then consider how to elect the cluster-heads and provide two algorithms for cluster-head election. Last, we implement all the protocols and perform the experiments for evaluating the protocols.

The efficiency of transportation system depends on many factors, such as traffic congestion, vehicle accidents and road conditions. To improve the reliability, productivity and safety of the system, many researchers propose to use a wireless sensor network (WSN) as a solution. A WSN usually consists of many tiny sensor nodes for sensing, data processing and communication. In this study, we present the development of a small-sized, low-power and lightweight wireless sensor node. It is equipped with a 3-axes accelerometer, an altimeter sensor, humidity sensor, temperature sensor, 315 MHz RF transceiver module and a typical coin-sized lithium battery (3.0 V, 220 mAh). The entire sensor node fits within a 28 × 20 × 8 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> volume and is only 7 grams (not including the antenna). An 8-bit MCU is included in the RF transceiver module to control sensor node operation. It collects and transmits sensors data in real time to the RF repeater with bit rate 24 kbps. During continuous operation, the sensor node consumes less than 3 mA current. Thus for a 220 mAh battery, the wireless sensor node can continue operating for more than 75 hours.

Wireless connection based smart sensors network can combine sensing, computation, and communication into a single, small device.Because sensor carries its own wireless data transceiver, the time and the cost for construction, maintenance, the size and weight of whole system have been reduced.Information collected from these sensor nodes is routed to a sink node via different types of wireless communication approaches.Healthcare systems have restricted the activity area of patients to be within the medical health care center or residence area.To provide more a feasible situation for patients, it is necessary to embed wireless communication technology into healthcare systems.The physiological signals are then immediately transmitted to a remote management center for analysis using wireless local area network.Healthcare service has been further extended to become mobile care service due to the ubiquity of global systems for mobile communications and general packet radio service.It is important that using sensors to detect field-environment signals in agriculture is understood since a long time ago.Precision agriculture is a technique of management of large fields in order to consider the spatial and temporal variability.To use more sophisticated sensor devices with capabilities of chemical and biological sensing not only aids the personnel in the field maintenance procedure but also significantly increases the quality of the agricultural product.In this chapter, we examine the fields in healthcare and precision agriculture based on wireless sensor networks.In the application of healthcare systems, a System on a Chip (SoC) platform and Bluetooth wireless network technologies were combined to construct a wireless network physiological signal monitoring system.In the application of precision agriculture, an SoC platform was also used combining the ZigBee technology to consist a field signals monitoring system.In addition to the two applications, the fault tolerance in wireless sensor networks is also discussed in this chapter.

Node placement for connected target coverage in wireless sensor networks with dynamic sinks

Wireless sensor network (WSN) is an important tool for large-scale field monitoring. It can acquire field information with various sensor nodes at high temporal and spatial resolution. In this paper, in order to accurately get the soil water deficit and then execute effective and water-saving irrigation, a WSN of soil moisture is established and the remote management platform is developed for data collection, storage, and analysis. The WSN of soil moisture system includes twenty sensor nodes, two sink nodes, and a high resolution web-camera. The sensor nodes are located in a corn field and send the data of soil moisture every 30 minutes to the sink node, which connected to a GPRS module. The GPRS module is used to forward the data to the remote management platform using TCP-IP standard protocol. The platform can be browsed in any computer connected with Internet. The distribution of the sensor nodes and all measured data can be read in the platform, which provides an irrigation prescription according to the measurements of soil moisture. The web-camera is used to monitor the corn field to provide images for precision management of the crop. Through a long-time test in field, it is proved that the whole system is stable and reliable, and can be used to support precision irrigation system.

Security plays a vital role in enabling future integration of Wireless Sensor Networks (WSNs) with the Internet. Although security in WSNs is a mature field of research and many proposals currently exist that can address particular security threats, how to guarantee end-to-end security at the network layer for IPv6-enabled WSNs remains an open research issue. Security should be addressed at the network layer, as sensor nodes will evolve to become IPv6 aware and new applications are adapted or designed that depend on IPv6 connectivity to sensor nodes. We propose and evaluate new compressed AH and ESP 6lowpan security headers that allow the protection of IPv6 communications on IEEE 802.15.4 WSNs. As the security headers are designed to work side-by-side with other extension headers of the 6lowpan adaptation layer, they allow also the establishment of end-to-end secure communications between Internet hosts and wireless sensor nodes. The usage of IPv6 on WSNs has the potential of enabling the integration of sensing applications with the Internet and, if end to end security is properly addressed, can represent a major contribution towards the internet of things.

This paper presents the design of wireless sensor network (WSN) based on low-power wide area network technology for high-tech agriculture. This WSN allows the farmer to collect data such as air temperature, air humidity, soil moisture. The WSN system consists of components: 02 wireless sensor nodes, 01 gateway, 01 cloud server and smartphone app. This WSN tested for data transmission in two zones: zone 1 (dense urban environments) at a distance of 500m and zone 2 (urban environments - less obstacles) at a distance of 1,500m and 1,700m. The data collected at different times of the day and updated every 15 minutes. The results show that the wireless sensor network system operates stably, data constantly updated to LoRa Server and there was not data packet loss. The power consumption of sensor node and gateway determined in three operating modes: transmitting, receiving, turn-off. This shows the advantages of LoRa technology in the development of wireless sensor network which is the distance of data transmission distance and low power consumption. Besides this WSN also tested in the net house of aquaponics of the Research Center for High-tech Application in Agriculture (RCHAA), University of Science, Vietnam National University-HCM. The results show that the WSN system is working reliably and promising which brings significantly benefits to smart agriculture as aquaponics, clean vegetable farms, aquaculture farms…

Wireless Sensor Networks (WSNs) are networks of small, low-cost, low-power, and wirelessly connected sensor nodes. These sensor nodes can be distributed over a large area and can collect data about the environment, such as temperature, humidity, light, sound, vibration, and motion. WSNs are useful in a variety of applications, including environmental monitoring, smart agriculture, healthcare, industrial automation, and security. They can be used to gather data in remote or hard-to-reach locations, and they can also be used to monitor large areas continuously and in real-time. The nodes in a WSN are typically battery-powered and have limited processing and communication capabilities. Therefore, energy efficiency is a critical concern in WSNs, and the nodes are designed to conserve energy wherever possible. Proper choice of Communication protocols are essential for energy conservation in Wireless Sensor Networks (WSNs).This paper discuss about various communication protocols and its types. They help to reduce idle listening time, minimize data transmission, optimize routing, and control transmission power. By using energy-efficient communication protocols, WSNs can achieve longer network lifetime, better data accuracy, and improved network performance.

Recent technological advances in microelectronics and nano-systems technologies have made it feasible to equip wireless sensor nodes with small low-cost cameras to capture and transmit video. Wireless video sensor networks are gaining popularity due to numerous potential applications such as video surveillance, environmental and habitat monitoring, and so on. However, due to the limited battery available in wireless video sensor nodes, provisioning of QoS in such a network is a challenging task. We provide a survey on the major issues related to QoS provisioning in wireless video sensor networks and possible solution approaches. A dynamic power management framework is proposed for a wireless video sensor node to improve energy saving performance so that the lifetime of the sensor node can be increased. This framework considers the video traffic arrival process in the sensor node, the sleep and wakeup processes in the camera and wireless transceiver electronics, the queue status, and the wireless channel condition. Performance analysis results show that the proposed mechanism can achieve considerable energy saving in a sensor node while providing a target level of QoS performance.

Various communication services have been provided. They include environmental monitoring and/or control, ad-hoc communication between mobile nodes, and inter-vehicle communication in intelligent transport systems. As a means of facilitating the above advanced communication services, autonomous decentralized networks, such as wireless sensor networks (Akyildiz et al., 2002; Rajagopalan & Varshney, 2006), mobile ad-hoc networks (Perkins & Royer, 1999; Johnson et al., 2003; Clausen & Jaquet, 2003; Ogier et al., 2003), and wireless mesh networks (Yamamoto et al., 2009), have been intensively researched with great interests. Especially, a wireless sensor network, which is a key network to construct ubiquitous information environments, has great potential as a means of realizing a wide range of applications, such as natural environmental monitoring, environmental control in residential spaces or plants, object tracking, and precision agriculture (Akyildiz et al., 2002). Recently, there is growing expectation for a new network service by a wireless sensor network consisting of a lot of static sensor nodes arranged in a service area and a few mobile robots as a result of the strong desire for the development of advanced systems that can flexibly function in dynamically changing environments (Matsumoto et al., 2009). In this chapter, a large scale and dense wireless sensor network made up of many static sensor nodes with global positioning system, which is a representative network to actualize the above-mentioned sensor applications, is assumed. In a large scale and dense wireless sensor network, generally, hundreds or thousands of static sensor nodes limited resources, which are compact and inexpensive, are placed in a service area, and sensing data of each node is gathered to a sink node by inter-node wireless multi-hop communication. Each sensor node consists of a sensing function to measure the status (temperature, humidity, motion, etc.) of an observation point or object, a limited function of information processing, and a simplified wireless communication function, and it generally operates on a resource with a limited power-supply capacity such as a battery. Therefore, a data gathering scheme and/or a routing protocol capable of meeting the following requirements is mainly needed to prolong the lifetime of a large scale and dense wireless sensor network composed of hundreds or thousands of static sensor nodes limited resources. 1. Efficiency of data gathering 2. Balance of communication load among sensor nodes 3. Adaptability to network topology changes

In wireless sensor network (WSN) application, one of the most important problems to be considered is power consumption. As a result, a number of methodologies or methods for analyzing the power consumption of the application have been presented. These methodologies may aid in the prediction of the lifespan of WSNs, the providing of suggestions to application developers, and the optimization of the amount of energy utilized by WSN applications. All of the sensors in wireless sensor nodes are rechargeable batteries devices with a limited amount of battery power available. It will be difficult to replace every power supply battery available in the network on an individual basis after deploying of sensor nodes. To sort out these issues, an efficient analyzing technique for analyzing the power consumption of WSN is proposed. In this research work, a prototype model with a simulation model is presented. The proposed research work may lower the amount of power used by each sensor node, while also increasing the life of sensors by shutting down certain of their components in order to achieve higher energy savings and longer life. It is necessary to do an analysis of the power usage of each sensor node before using this power management strategy. As a result of this, the proposed method analyzes the WSN power consumption in real time manner.