Integration Of Wireless Sensor Networks Research Articles

Deep Learning-Based Medical Information System in First Aid of Surgical Trauma.

The aim of this study was to explore the application of process reengineering integration in trauma first aid based on deep learning and medical information system. According to the principles and methods of process reengineering, based on the analysis of the problems and causes of the original trauma first aid process, a new set of trauma first aid integration process is established. The Deep Belief Network (DBN) in deep learning is used to optimize the travel path of emergency vehicles, and the accuracy of travel path prediction of emergency vehicles under different environmental conditions is analyzed. DBN is applied to the surgical clinic of the hospital to verify the applicability of this method. The results showed that in the analysis of sample abscission, the abscission rates of the two groups were 2.23% and 0.78%, respectively. In the analysis of the trauma severity (TI) score between the two groups, more than 60% of the patients were slightly injured, and there was no significant difference (P > 0.05). In the comparative analysis of treatment effect and family satisfaction between the two groups, the proportion of rehabilitation patients in the experimental group (55.91%) was significantly better than that in the control group, and the satisfaction of the experimental group (7.93 ± 0.59) was significantly higher than that of the control group (5.87 ± 0.43) (P < 0.05). Therefore, integrating Wireless Sensor Network (WSN) measurement and process reengineering under the medical information system provides feasible suggestions and scientific methods for the standardized trauma first aid.

An Analytical Survey of WSNs Integration with Cloud and Fog Computing

Wireless sensor networks (WSNs) are spatially scattered networks equipped with an extensive number of nodes to check and record different ecological states such as humidity, temperature, pressure, and lightning states. WSN network provides different services to a client such as monitoring, detection, and runtime decision-making against events occurrence. However, the WSN network still has some limitations in computing power, storage resources, and battery life, which make the network is restricted for data transformation. It is due to less supportive battery power, and limited memory of nodes. The integration of WSN and cloud offers an open, adaptable, and more reconfigurable stage for different security checks and regulating requirements. In this paper, we discovered how WSN and cloud computing (CC) are integrated and help to accomplish different goals. Additionally, a comprehensive study about procedures and issues for an effective combination of WSN-CC is presented. This work also presents the work proposed by the research community for WSN-CC. Besides, we explored the integration of WSN/IoT with Fog computing (FC). Based on investigations, WSN integration with Fog computing (FC) has many benefits with respect to latency, energy consumption, data processing, and real-time data streaming. FC is not a substitute for distributed computing, so far it is utilized to improve the productivity of the sensor.

Lightweight method of shuffling overlapped data-blocks for data integrity and security in WSNs

Wireless Sensor Networks (WSN) consist of devices with limited resources to explore and sense the environment in a cooperative way. Security, mainly in terms of guaranteeing the data integrity, is a primary issue for many applications, but with an extra energy cost. Thus, trade-off is required between security level and energy consumption in real applications. First of all, a brief survey about security methods, focusing in data integrity, in WSN is implemented. The objective of this paper is to propose a new data integrity method with medium security levels and low energy cost. Therefore, we propose a new and lightweight mechanism for data integrity with overlapping blocks in WSNs. Hence, an attacker will spend much time and effort to interpret and alter the packets. The experiments were performed using TinyOS 2.1 operating system and TelosB nodes for measuring the overhead in terms of energy consumption, memory, and packet size. Moreover, the receiver is able to detect tampering packets and request those retransmission data. An attacker would require huge amounts of memory and processing time to extract the original information, even for small-sized data blocks. Thus, this fact makes this approach a simple, yet effective, mechanism to protect data whilst enhancing the data integrity.

A Survey of QoS-aware Routing Protocols for the MANET-WSN Convergence Scenarios in IoT Networks

Wireless Sensor Network (WSN) and Mobile Ad hoc Network (MANET) have attracted a special attention because they can serve as communication means in many areas such as healthcare, military, smart traffic and smart cities. Nowadays, as all devices can be connected to a network forming the Internet of Things (IoT), the integration of WSN, MANET and other networks into IoT is indispensable. We investigate the convergence of WSN and MANET in IoT and consider a fundamental problem, that is, how a converged (WSN-MANET) network provides quality of service (QoS) guarantees to rich multimedia applications. This is very important because the network performances of WSN and MANET are quite low, while multimedia applications always require quality of services at certain levels. In this work, we survey the QoS-guaranteed routing protocols for WSN-MANETs, that are proposed in IEEE Xplore Digital Library over the last decade. Then, basing on our findings, we suggest future open research directions.

Practical Identity Based Online/Off-Line Signcryption Scheme for Secure Communication in Internet of Things

Contemporary developments in providing proper security in the Internet of Things (IoT) have been made signcryption scheme highly suitable for various applications such as smart cities, smart healthcare and smart agriculture. However, security and privacy are the primary concerns in protecting data as it was highly sensitive. This paper is proposing a new Identity based online/off-line signcryption scheme suitable to provide secure message communication among IoT devices, gateway, and the server. This method is divided into the online and offline phases, where heavy mathematical computations are carried out in the offline phase and light computations in the online phase. This scheme provides a security solution for integrating Wireless Sensor Networks (WSNs) into the IoT. Experimentation was done and finally compared against existing techniques and proved that the proposed mechanism reduces the computation time in online by performing a greater number of operations in off-line signcryption phase. Further, it provides indistinguishability against adaptive chosen ciphertext attacks and existential unforgeability against adaptive chosen messages attacks.

A novel communication framework between MANET and WSN in IoT based smart environment

Internet of Things (IoT) has become an emerging platform for connecting real-world objects for desired service provisioning via the Internet. The real-world devices or objects in IoT enable a smart environment with the help of Mobile Ad hoc Networks (MANETs) and Wireless Sensor Networks (WSNs). However, the integration of MANET and WSN in the IoT environment requires a flexible and unified framework for efficient and secure communication between intelligent objects or devices. The state-of-art works in this direction lack standard communication framework for effective implementation of MANET with WSN. In this paper, an efficient and secure communication framework for interconnecting MANET and WSN devices is presented. The proposed communication framework comprises different phases such as collecting data using sensors, sending the data to data processing centers via the mobile access points and finally forwarding the data to data centers for analysis, decision making and reporting purposes. The proposed integration solution is discussed in detail and is evaluated with a case study on data harvesting in rural areas. The efficacy of the proposed framework is reported which will significantly drive the integration of MANET and WSN in future internet using smart objects.

WSNs and IoT Their Challenges and applications for Healthcare and Agriculture: A Survey

Nowadays, the Wireless Sensor Network (WSN) has materialized its working areas, including environmental engineering, agriculture sector, industrial, business applications, military, intelligent buildings, etc. Sensor networks emerge as an attractive technology with great promise for the future. Indeed, issues remain to be resolved in the areas of coverage and deployment, scalability, service quality, size, energy consumption and security. The purpose of this paper is to present the integration of WSNs for IoT networks with the intention of exchanging information, applying security and configuration. These aspects are the challenges of network construction in which authentication, confidentiality, availability, integrity, network development. This review sheds some light on the potential integration challenges imposed by the integration of WSNs for IoT, which are reflected in the difference in traffic features.

Cluster-tree based energy efficient data gathering protocol for industrial automation using WSNs and IoT

Abstract Integrating Wireless Sensor Networks (WSNs) and the Internet of Things (IoT) is to build a heterogeneous device network for connecting, sharing and storing their information in order to create the application environment as smart. It also helps in industrial automation to predict and build a fault-tolerant environment. The automation of industry can be made possible with the emergence of new developments in sensor manufacturing and communication. In this paper, a Cluster-Tree based Energy Efficient Data Gathering (CTEEDG) protocol is proposed to increase the lifetime and throughput of WSNs. The CTEEDG uses the Fuzzy logic to select the Cluster Head (CH) based on the information collected locally. In the inter-cluster communication phase, the tree topology is established between the clusters towards the Base Station (BS) which ensures the availability of the congestion free shortest path to the BS. From the simulation results, the proposed CTEEDG outperforms the FAMACROW and DL-LEACH by 28.81% and 38.28% in terms of throughput. And also, the proposed method has 29.26% and 49.29% reduction in average energy consumption when compared to the FAMACROW and DL-LEACH.

A Privacy-Preserving Authentication, Authorization, and Key Agreement Scheme for Wireless Sensor Networks in 5G-Integrated Internet of Things

Wireless sensor networks (WSNs) have played an important role in the Internet of Things (IoT), and the 5G network is being considered as a major candidate for IoT's communication network with the advent of 5G commercialization. The potential of integrating WSNs and 5G in the IoT is expected to allow IoT to penetrate deeply into our daily lives and to provide various services that are convenient, but at the same time, it also brings new security threats. From this aspect, user authentication and key agreement are essential for secure end-to-end communication. As IoT devices, including sensors, collect and process more and more personal information, both anonymous authentication and authorization are also required to protect the privacy and to prevent anyone without privileges from accessing private data. Recently, Adavoudi-Jolfaei et al. proposed an anonymous three-factor authentication and access control scheme for real-time applications in WSNs. However, we found that this scheme does not provide sensor-node anonymity and suffers from user collusion and desynchronization attacks. In this paper, we introduce a system architecture by considering the integration of WSNs and 5G for IoT. Based on a cryptanalysis of Adavoudi-Jolfaei et al.'s scheme and the system architecture, we propose an elliptic curve cryptography (ECC)-based privacy-preserving authentication, authorization, and key agreement scheme for WSNs in 5G-integrated IoT. We conduct a formal and informal security analysis in order to demonstrate that the proposed scheme withstands various security attacks and guarantees all desired security features, overcoming the drawbacks of Adavoudi-Jolfaei et al.'s scheme. Finally, a performance and comparative analysis with the related schemes indicate that the proposed scheme is both efficient and more secure.

Efficient Data Collection using Mobile Sink Scheme in IoT

Wireless sensor networks (WSNs) have become increasingly important in the informative development of communication technology. The growth of Internet of Things (IoT) has increased the use of WSNs in association with large scale industrial applications. The integration of WSNs with IoT is the pillar for the creation of an inescapable smart environment. A huge volume of data is being generated every day by the deployment of WSNs in smart infrastructure. The collaboration is applicable to environmental surveillance, health surveillance, transportation surveillance and many more other fields. A huge quantity of data which is obtained in various formats from varied applications is called big data. The Energy efficient big data collection requires new techniques to gather sensor-based data which is widely and densely distributed in WSNs and spread over wider geographical areas. In view of the limited range of communication and low powered sensor nodes, data gathering in WSN is a tedious task. The energy hole is another considerable issue that requires attention for efficient handling in WSN. The concept of mobile sink has been widely accepted and exploited, since it is able to effectively alleviate the energy hole problem. Scheduling a mobile sink with energy efficiency is still a challenge in WSNs time constraint implementation due to the slow speed of the mobile sink. The paper addresses the above issues and the proposal contains four-phase data collection model; the first phase is the identification of network subgroups, which are formed due to a restricted range of communication in sensor nodes in a wide network, second is clustering which is addressed on each identified subgroup for reducing energy consumption, third is efficient route planning and fourth is based on data collection. The two time-sensitive route planning schemes are presented to build a set of trajectories which satisfy the deadline constraint and minimize the overall delay. We have evaluated the performance of our schemes through simulation and compared them with the generic enhanced expectation-maximization (EEM) mobility based scenario of data collection. Simulation results reveal that our proposed schemes give much better results as compared to the generic EEM mobility approach in terms of selected performance metrics such as energy consumption, delay, network lifetime and packet delivery ratio.

NOSS (novel optimal sleep scheduling) scheme for energy and data reliability optimisation in mobile cloud‐assisted wireless sensor networks

MCC is one of the best opportunities to provide reliable data transmission to the users in mobility through integration with wireless sensor networks (WSNs), and this integration of MCC–WSN enables the mobile user to receive all communication in the digitised form. Many researchers proposed the MCC–WSN integration scheme to concentrate on the delay and energy trade-off instead of a novel optimal sleep scheduling (NOSS) scheme proposed for energy and reliability optimisation and it has three-fold uses in implementation: (i) a selective optimal data forward method used to forward the gathered data in selective custom, which maximises the data reliability; (ii) an improved fish swarm optimisation algorithm is used to compute the awake or asleep status of each sensor node, which minimises the energy consumption; (iii) a partial priority-based decision-making algorithm is used to compute the best request received from the user among multiple requests. In addition, the NOSS scheme would gather and forward data in a more reliable, energy-efficient way without affecting the scalability with robustness in comparison with the existing schemes. Simulation results demonstrate the effectiveness of the proposed NOSS scheme in enhancing the usefulness of energy consumption and data reliability of WSNs.

Energy harvesting using thermoelectricity for IoT (Internet of Things) and E-skin sensors

With the increasing demand for Internet of Things (IoT) with integrated wireless sensor networks (WSNs), sustainable power supply and management have become important issues to be addressed. Thermal energy in forms of waste heat or metabolic heat is a promising source for reliably supplying power to electronic devices; for instance, thermoelectric power generators are widely being researched as they are able to convert thermal energy into electricity. This paper specifically looks over the application of thermoelectricity as a sustainable power source for IoT including WSNs. Also, we discuss a few thermoelectric systems capable of operating electronic skin (e-skin) sensors despite their low output power from body heat. For a more accurate analysis on body heat harvesting, models of the human thermoregulatory system have been investigated. In addition, some clever designs of heat sinks that can be integrated with thermoelectric systems have also been introduced. For their power management, the integration with a DC–DC converter is addressed to boost its low output voltage to a more usable level.

Implementation of Wireless Sensor Network (WSN) to calculate air pollution index of Samarinda City

Environmental pollution is one of the major problems opened by the world today. The main problem of this pollution, is decreasing air quality. This decrease in air quality is caused by many things, from excessive environmental exploitations, industrial activity, energy use, until the exhaust emissions of vehicles all of which trigger into pollution problems. So far Indonesian government has purchased and use the Air Quality Monitoring Base Station to measure different types of air pollutants. However, field statistics data show that the minimum quality of air quality measuring devices in each city is not commensurate with the minimum recommended amount, ideally one base station is used for 200.000 inhabitans. In this research, we developed an integrated Wireless Sensor Network to monitor the concentration of air pollution. Implemented fifteen sensor nodes which each node contains CO and NO2 sensors to sensing from the environment. the collected data will be used to calculate the standard air pollution index of samarinda city. The data is stored in server and we can publish for public to access information throught a gadget and thing speak server.

Sustainable and Efficient Data Collection from WSNs to Cloud

The development of cloud computing pours great vitality into traditional wireless sensor networks (WSNs). The integration of WSNs and cloud computing has received a lot of attention from both academia and industry. However, collecting data from WSNs to cloud is not sustainable. Due to the weak communication ability of WSNs, uploading big sensed data to the cloud within the limited time becomes a bottleneck. Moreover, the limited power of sensor usually results in a short lifetime of WSNs. To solve these problems, we propose to use multiple mobile sinks (MSs) to help with data collection. We formulate a new problem which focuses on collecting data from WSNs to cloud within a limited time and this problem is proved to be NP-hard. To reduce the delivery latency caused by unreasonable task allocation, a time adaptive schedule algorithm (TASA) for data collection via multiple MSs is designed, with several provable properties. In TASA, a non-overlapping and adjustable trajectory is projected for each MS. In addition, a minimum cost spanning tree (MST) based routing method is designed to save the transmission cost. We conduct extensive simulations to evaluate the performance of the proposed algorithm. The results show that the TASA can collect the data from WSNs to Cloud within the limited latency and optimize the energy consumption, which makes the sensor-cloud sustainable.

Energy Efficient Encryption Scheme for Integrating Wireless Sensor Networks with Internet

Energy Efficient Encryption Scheme for Integrating Wireless Sensor Networks with Internet

Smart Irrigation System Using Wireless Sensor Network with Cooja and Contiki

Automated irrigation systems are important for improving agricultural productivity, and such systems can be improved through the use of wireless sensor networks (WSN) for detecting and relaying critical information including location-specific temperature, humidity, light, etc. These measurements can then be used to produce more accurate data-driven decisions. This paper presents a smart irrigation system integrating wireless sensor network and using a low power and lossy network (RPL) protocol. Irrigation supply decisions are made in real time, based on data simulated using the Cooja simulator and Contiki operating system. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License .

Integration of internet of things with wireless sensor network

&lt;p&gt;The Internet of things (IoT) is a major source for technology solutions in many industries. The IoT can consider, Wireless Sensor Network (WSN) as the backbone network to reduce formation or advent of new technology. Integration of these would reduce the burden and form smart sensor node network with nodes given access to internet. WSN is already a major legacy system that has percolated into many industries. Thus by integration of IoT and WSN no huge paradigm shift is needed for the industries.&lt;/p&gt;

Low Delay Technology Research of Transmission Line Tower Monitoring Network Integrating WSN and RFID

The tower is a key component of the transmission line system and its stability and reliability is the guarantee for the safety of entire transmission line system. This paper proposes a transmission tower monitoring network integrating wireless sensor network (WSN) and radio frequency identification (RFID). Compared to current designs, the proposed monitoring network shows the advantages of low cost, fast fault locating, tracking and management of grid equipment, and long-time monitoring. Low delay design is critical for the proposed monitoring network. In order to achieve balance between transmission delay and network cost, this paper establishes the transmission delay model for sink node optimization. For the redundant data of RFID, this paper presents a novel data cleaning scheme specially for the transmission tower monitoring, which can effectively reduce the redundant data at the reader end. The simulation results show that the optimal group number is 10 according to the proposed delay model.

Analysis of estimator and energy consumption with multiple faults over a distributed integrated wireless sensor network

In this paper, based on event-triggered mechanism, a new state estimation algorithm is proposed for monitoring of pollutants in aircraft cabins. According to the actual environment of the aircraft cabin, the algorithm considers the influence of path loss and packet loss on the algorithm in monitoring system and can effectively monitor the pollutant concentration and save energy. The sufficient conditions for the stability of the algorithm have been proved in this paper and the influence of the triggered threshold on the energy consumption of the algorithm is analysed. Finally, the simulation proves that compared with the existing Kalman-consensus filter, the proposed algorithm has stronger fault tolerance and lower energy consumption, and energy consumption and accuracy of the algorithm can be controlled by adjusting the triggered threshold according to actual needs.

Assessment of Wave-Guided Ultrasonic Transducer System for Erosion-Corrosion Detection in Nuclear Applications

Abstract Storage tanks and pipelines are used at nuclear waste sites across the Department of Energy (DOE) complex to store and transfer nuclear wastes. One of the significant aspects in such sites is monitoring the structural integrity of the waste transfer pipelines and the storage tanks. Literature indicates that the industry standard method of thickness measurements using ultrasonic sensors is mainly through manual inspections. As such, this procedure is expensive and exhaustive for nuclear applications. Hence, in this research, the authors assess a wave guided ultrasonic sensor system for erosion-corrosion (thickness change) detection in waste transfer pipelines at Hanford nuclear waste site. This ultrasonic transducer (UT) sensor system (from Permasense, a UK based manufacturer [2]) has the advantage of real-time remote monitoring. It is an integrated wireless sensor network system which uses a patented technology for the acoustic wave propagation and has proven applications in the oil and gas industries [3]. This UT sensor system meets the requirement of providing the actual thickness measurement in pipes, is capable for 2 inch pipes and elbows, and is customized for mounting with a mechanical clamping system. The sensors are also capable of operating at high temperatures up to 600°C (1100°F). This is due to their patented waveguide technology that holds the sensor head (containing ultrasonic transducers, electronics, and battery) away from the hot metal surface. The sensor's measurements are transmitted wirelessly back to a gateway (wireless access point) mounted near the main unit. Since there is no cost associated with measurement acquisition or measurement retrieval, the frequency of measurement can be configured to be as frequent as every 15 minutes. Connection of the gateway to the operator's existing information technology infrastructure allows the data to be viewed from personnel desks. Sensor battery life of up to 10 years allows continuous data delivery between turnarounds without access to a sensor's physical location. The sensor model chosen for the present research (testing and validation) is the WT 210 series [2]. It consists of the 304 stainless steel wave guides, sensor head, antenna, battery and a stabilizer. In addition there is a built in thermocouple probe to monitor the pipe surface temperature which also allows the wall thickness measurement to be temperature compensated when required. The sensors communicate using a customized wireless protocol, creating a self-forming and self-managing wireless mesh, which delivers continuous wall thickness measurements of the highest integrity and accuracy directly to the end user. Scope of the present research includes the initial verification and validation of the Permasense Guided Wave sensor system as a potential erosion/corrosion detection system for carbon steel pipelines under static conditions. The real-time erosion/corrosion detection is also investigated by measuring the thinning of the pipe sections by circulating simulants and continuous monitoring. This is achieved by passing abrasive solutions through an in-house designed pipe loop system. The loop has been designed to replicate the sections and carbon steel pipe material similar to the existing system at Hanford site. Varying concentrations of sand and water mixture is used as an eroding agent [5]. The erosion experiments are conducted for several months and the results obtained provide realistic wear rates on 2 inch and 3 inch carbon steel pipes with straight sections and elbows using the Permasense UT sensor system. Thus, the present research delivers solutions for sensor evaluations and conducts bench scale testing followed by data acquisition and analysis for corrosion and erosion assessment. This assessment of the UT sensor system will be useful for monitoring the real-time thinning of the waste transfer pipelines and to deliver more realistic estimates of the remaining useful life of the components and incorporate those estimates into future design/testing plans across the nuclear waste sites.