Wireless Sensors Network Using Machine Learning Approach

So we will definitely need to have a base station that controls all the sensors and makes sure that it uses encryption to secure communication. We will have authentication, so that we can ensure data integrity and origin and to prevent injection of unauthorized messages. Use confidentiality, so that we can ensure secrecy of data and prevent eavesdropping. To accomplish this we are going to use Sensor-Network Encryption Protocol (SNEP) and micro Timed Efficient Stream Loss-tolerant Authentication

A WSN is a type of wireless networks that consists of collection sensor nodes which are tiny devices. Each sensor node of the network has different processing capability. It may contain multiple types of memory (program, data and flash memories), have a RF transceiver, have a power source (e.g., batteries and solar cells), and accommodate various sensors and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an ad hoc fashion [13, 14]. Optimum need of each sensor node is to maximize its own utility function. Also the whole network requires resource assignments balance to perform in a useful and efficient way. This chapter presents a brief survey on WSNs showing its types, characterizing features, protocols and applications.

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The concept of understanding “ knowledge and truth corresponds to the whole of our hermeneutic experience” (Gadamer, 2013 p.250). In this essay, I aim to address Gadamerian philosophical hermeneutics under conditions to “support consciousness that informs us of our relationship with the environment ”(Clingerman, Treanor, Drenthen, & Utsler,2013, p.4). I will provide an a short historical background of hermeneutics particular to the function of the religious text. For the long term goal, I examine air quality as an environmental hermeneutic issue by connecting to Gadamer’s argument “ that understanding belongs to the specific nature of our human life.( Gadamer,2014).

A mobile wireless sensor network, shortly WMSN, can be defined as a wireless network of a sensor nodes that are mobile. Motivation behind a mobile wireless sensor network is to capture real world data and convert them so it can be transferred, processed, stored and later studied or analyzed (Guo, 2014). The MWSN is usually a combination of two or more technologies such as mobility, wireless connectivity and the ability to gather local information. The mobile wireless sensor network is usually deployment of a large number of small, inexpensive, self-powered nodes and receiving station (Kumbhare, Rangaree, & Asutkar, 2016). These MWSN can be effectively used for civil and military purposes.

Abstract— Wireless sensor networks (WSNs) is the collection of physical measurements in a geographical area. It tracks the spatial-average of the sensor measurements in a region. Since it is highly vulnerable to sensor faults and measurement noise the average operation is not robust. In this paper the proposed computational efficient method is used to compute a weight average of sensor measurement. It takes consideration of sensor faults and sensor noise. WSN uses random projections of sensor to compress data and send the compressed data to the data fusion center. The computation efficient method uses the data fusion center for direct work with the compressed data stream. The fusion center performed decompression at the time of computed weighted average. Thus, it reduces the computational requirements. Hence the proposed method gives better accuracy and more efficient for the WSN.

A Wireless Sensor Network (WSN) is comprised of multiple tiny devices called nodes or motes. These are distributed spatially in an environment to monitor sense and compute data wirelessly. The role of a sensor node is to evaluate different tasks. First, a node has to sense physical conditions and exchange the information with other nodes after computation. Second, it plays the important role of being a relay for different sensor nodes [1],[2],[3],[4]. These nodes can mount anywhere in the environment [2]. With recent advancements in the field of electronics these devices are becoming cheaper and smaller and are being employed in both indoor and outdoor environments. Applications include agricultural monitoring, household and military surveillance, industrial automation and robotics, and healthcare [3]. A sensor node, shown in Figure.1 is a low power device and consists of five different components namely [5], [12]

Wireless Sensor Networks refers to incredibly distributed networks of small and lightweight wireless nodes with very confined capabilities, deployed in large numbers in an open environment to monitor the environmental conditions by measuring physical parameters such as temperature, pressure, humidity etc. Each and every node (sensor) has a microprocessor and a small amount of memory for sensing, signal processing and for communication purposes. Each sensor node communicates wirelessly with different regional nodes within its radio conversation range. Deployment of WSN’s evade installation costs however at the same time power efficiency as a main challenge. A scheme of a wireless sensor node connected to the internet is shown in Fig. 1: wireless sensor networks ordinarily contains sensing unit, processing unit, transmission unit and power unit.

Wireless sensor network (WSN) is an infrastructure less, dynamic topology, application oriented, multihoping network design with small, sensing wireless distributed nodes. [1] WSN consists of thousand of wireless node distributed in a geographical area. The distributed nodes senses the current status of its region and supply to the next upper which collects different information from different nodes and supplied final information to the

Due to the advancement in micro-electro-mechanical systems and microelectronics and correspondingly wide applications of wireless sensor networks, there has been given tremendous attentions by researchers in recent years. In result there is development of low-cost, low-power, multifunctional sensor nodes that are small in size and communicate untethered in short distances. These tiny sensor nodes, which consist of sensing, data processing, and communicating components, leverage the idea of sensor networks based on collaborative effort of a large number of nodes. Sensor nodes in such a network are often powered with onboard batteries with limited energy. It is impractical or infeasible to replenish energy via replacing batteries on these sensors in most applications. As a result, it is well perceived that a sensor network should be deployed with high density in order to prolong the network lifetime. A sensor network is composed of a large number of sensor nodes, which are densely deployed either inside the phenomenon or very close to it. The position of sensor nodes need not be engineered or pre-determined. This allows random deployment in inaccessible terrains or disaster relief operations. On the other hand, this also means that sensor network protocols and algorithms must possess self-organizing capabilities. Another unique feature of sensor networks is the cooperative effort of sensor nodes. Sensor nodes are fitted with an on-board processor. Instead of

Abstract — Wireless sensor networks are being widely used in many surveillance applications. Since sensor nodes are a critical part of sensor networks, certain level of protection needs to be provided to them. The self-protection problem focuses on using sensor nodes to provide protection to themselves instead of the target objects or certain target area so that the sensor nodes can resists the attacks targeting to them directly. In this paper we compare paper [1] and paper [2]. The key research question being asked, how

A wireless sensor network can be composed of a large number of nodes, constituting a

The collection of sensor nodes by enabling cooperation, coordination and collaboration among sensor nodes is formed Wireless Sensor Network (WSN); the WSN consists of multiple autonomous nodes with a base station.

In this work, The field of wireless sensor systems have turned into a concentration of serious research as of late, particularly to monitor and describing of expansive physical situations, and for following different ecological or physical conditions, for example, temperature, weight, wind and dampness. Wireless Sensor systems can be utilized as a part of numerous applications, for example, untamed life observing, military target following and investigation, risky situation investigation, and tragic event alleviation. The immense measure of detected information of course ordering them turns into a basic assignment in a large portion of these applications.

Our goal is to analyze the network security problems of the Internet of Things and to find a possible solution for the problem.