A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

MLP neural network based gas classification system on Zynq SoC

Systems based on Wireless Gas Sensor Networks (WGSN) offer a powerful tool to observe and analyse data in complex environments over long monitoring periods. Since the reliability of sensors is very important in those systems, gas classification is a critical process within the gas safety precautions. A gas classification system has to react fast in order to take essential actions in case of fault detection. This paper proposes a low latency real-time gas classification service system, which uses a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN) to detect and classify the gas sensor data. An accurate MLP is developed to work with the data set obtained from an array of tin oxide (SnO2) gas sensor, based on convex Micro hotplates (MHP). The overall system acquires the gas sensor data through RFID, and processes the sensor data with the proposed MLP classifier implemented on a System on Chip (SoC) platform from Xilinx. Hardware implementation of the classifier is optimized to achieve very low latency for real-time application. The proposed architecture has been implemented on a ZYNQ SoC using fixed-point format and achieved results have shown that an accuracy of 97.4% has been obtained

Intrusion tolerant routing with data consensus in wireless sensor networks

Dissertação para obtenção do Grau de Mestre em Engenharia InformáticaWireless sensor networks (WSNs) are rapidly emerging and growing as an important new area in computing and wireless networking research. Applications of WSNs are numerous, growing, and ranging from small-scale indoor deployment scenarios in homes and buildings to large scale outdoor deployment settings in natural, industrial, military and embedded environments. In a WSN, the sensor nodes collect data to monitor physical conditions or to measure and pre-process physical phenomena, and forward that data to special computing nodes called Syncnodes or Base Stations (BSs). These nodes are eventually interconnected, as gateways, to other processing systems running applications. In large-scale settings, WSNs operate with a large number of sensors – from hundreds to thousands of sensor nodes – organised as ad-hoc multi-hop or mesh networks, working without human supervision. Sensor nodes are very limited in computation, storage, communication and energy resources. These limitations impose particular challenges in designing large scale reliable and secure WSN services and applications. However, as sensors are very limited in their resources they tend to be very cheap. Resilient solutions based on a large number of nodes with replicated capabilities, are possible approaches to address dependability concerns, namely reliability and security requirements and fault or intrusion tolerant network services. This thesis proposes, implements and tests an intrusion tolerant routing service for large-scale dependable WSNs. The service is based on a tree-structured multi-path routing algorithm, establishing multi-hop and multiple disjoint routes between sensors and a group of BSs. The BS nodes work as an overlay, processing intrusion tolerant data consensus over the routed data. In the proposed solution the multiple routes are discovered, selected and established by a self-organisation process. The solution allows the WSN nodes to collect and route data through multiple disjoint routes to the different BSs, with a preventive intrusion tolerance approach, while handling possible Byzantine attacks and failures in sensors and BS with a pro-active recovery strategy supported by intrusion and fault tolerant data-consensus algorithms, performed by the group of Base Stations

Wireless distributed intelligence in personal applications

Tietokoneet ovat historian kuluessa kehittyneet keskustietokoneista hajautettujen, langattomasti toimivien järjestelmien suuntaan. Elektroniikalla toteutetut automaattiset toiminnot ympärillämme lisääntyvät kiihtyvällä vauhdilla. Tällaiset sovellukset lisääntyvät tulevaisuudessa, mutta siihen soveltuva tekniikka on vielä kehityksen alla ja vaadittavia ominaisuuksia ei aina löydy. Nykyiset lyhyen kantaman langattoman tekniikan standardit ovat tarkoitettu lähinnä teollisuuden ja multimedian käyttöön, siksi ne ovat vain osittain soveltuvia uudenlaisiin ympäristöälykkäisiin käyttötarkoituksiin. Ympäristöälykkäät sovellukset palvelevat enimmäkseen jokapäiväistä elämäämme, kuten turvallisuutta, kulunvalvontaa ja elämyspalveluita. Ympäristöälykkäitä ratkaisuja tarvitaan myös hajautetussa automaatiossa ja kohteiden automaattisessa seurannassa. Tutkimuksen aikana Seinäjoen ammattikorkeakoulussa on tutkittu lyhyen kantaman langatonta tekniikkaa: suunniteltu ja kehitetty pienivirtaisia radionappeja, niitten ohjelmointiympäristöä sekä langattoman verkon synkronointia, tiedonkeruuta ja reititystä. Lisäksi on simuloitu eri reititystapoja, sisäpaikannusta ja kaivinkoneen kalibrointia soveltaen mm. neurolaskentaa. Tekniikkaa on testattu myös käytännön sovelluksissa. Ympäristöälykkäät sovellusalueet ovat ehkä nopeimmin kasvava lähitulevaisuuden ala tietotekniikassa. Tutkitulla tekniikalla on runsaasti uusia haasteita ihmisten hyvinvointia, terveyttä ja turvallisuutta lisäävissä sovelluksissa, kuten myös teollisuuden uusissa sovelluksissa, esimerkiksi älykkäässä energiansiirtoverkossa.The development of computing is moving from mainframe computers to distributed intelligence with wireless features. The automated functions around us, in the form of small electronic devices, are increasing and the pace is continuously accelerating. The number of these applications will increase in the future, but suitable features needed are lacking and suitable technology development is still ongoing. The existing wireless short-range standards are mostly suitable for use in industry and in multimedia applications, but they are only partly suitable for the new network feature demands of the ambient intelligence applications. The ambient intelligent applications will serve us in our daily lives: security, access control and exercise services. Ambient intelligence is also adopted by industry in distributed amorphous automation, in access monitoring and the control of machines and devices. During this research, at Seinäjoki University of Applied Sciences, we have researched, designed and developed short-range wireless technology: low-power radio buttons with a programming environment for them as well as synchronization, data collecting and routing features for the wireless network. We have simulated different routing methods, indoor positioning and excavator calibration using for example neurocomputing. In addition, we have tested the technology in practical applications. The ambient intelligent applications are perhaps the area growing the most in information technology in the future. There will be many new challenges to face to increase welfare, health, security, as well as industrial applications (for example, at factories and in smart grids) in the future.fi=vertaisarvioitu|en=peerReviewed

Reefer container monitoring system based on WSN and cloud technology

Reefer containers are the main transportation method for the import and export of food and medicine. For high-quality products is necessary to monitor the condition of the reefer containers in order to avoid affecting goods quality due to environmental variations. Monitoring the reefer containers which are used to transport fruits, vegetables, and dairy products is one of the examples. In this context appears the necessity to develop this work expressed by a distributed sensor system for monitoring reefer containers. With the support of the WSN (wireless sensor network) including a set of sensors, it is possible to obtain the information about the temperature, humidity and location data of the reefer container and upload those data to a cloud platform expressed in the case of the purposed system by The Things Network platform. Based on LEACH (Low Energy Adaptive Clustering Hierarchy) routing algorithm, the embedded software was developed to guarantee a well-balanced distribution of the energy load among WSN end-nodes. A web application and a mobile application has been developed to display the data coming from the WSN node. To check if the reefer container working in a good condition, an alarm software module has been developed to highlight abnormal data coming for the system. The routing algorithm has been simulated and the effectiveness of the algorithm is verified by simulation results. The effectiveness of the proposed system was experimentally tested, and several results are included in this dissertation.Os contentores frigoríficos são o principal método de transporte para a importação e exportação de alimentos e medicamentos. Em produtos de alta qualidade, é necessário monitorizar as condições dos contentores frigoríficos, a fim de evitar a perda da qualidade das merca dorias devido a variações térmicas. Por exemplo, monitorarizando os contentores frigoríficos usados para transportar frutas, vegetais e laticínios. Neste contexto, aparece a necessidade do desenvolvimento deste projeto descrito por um sistema de sensores distribuídos para monitorizar contentores frigoríficos. Com o suporte da rede de sensores sem fios, incluindo um conjunto de sensores, é possível obter informações sobre os dados da temperatura, humidade e localização do contentor refrigerado e fazer uplo ad desses dados numa plataforma em cloud expressa no caso do sistema proposto por plataforma de rede de coisas. Com base no algoritmo de roteamento LEACH, o software incorporado foi desenvolvido para garantir uma distribuição equilibrada da carga de energi a entre os nós de WSN. Uma aplicação Web e uma aplicação móvel foram desenvolvidas para mostrar os dados provenientes do nó WSN. Para verificar a qualidade dos dados, um módulo de software de alarme foi também desenvolvido para destacar dados anormais que chegam ao sistema. O algoritmo de roteamento foi simulado e a eficiência do algoritmo é verificada pelos resultados da simulação. A eficiência do sistema proposto foi testada experimentalmente e os vários resultados estão incluídos nesta dissertação

TP-DS: A Heuristic Approach for Traffic Pattern Discovery System in MANET’s

As mobile ad hoc network (MANET) systems research has matured and several testbeds have been built to study MANETs, research has focused on developing new MANET applications such as collaborative games, collaborative computing, messaging systems, distributed security schemes, MANET middleware, peer-to-peer file sharing systems, voting systems, resource management and discovery, vehicular computing and collaborative education systems. Many techniques are proposed to enhance the anonymous communication in case of the mobile ad hoc networks (MANETs). However, MANETs are vulnerable under certain circumstances like passive attacks and traffic analysis attacks. Traffic analysis problem expose some of the methods and attacks that could infer MANETs are still weak under the passive attacks. In this Research, proposed ‘Traffic pattern Discovery System in MANET’s, aheuristic approach(TP-DS) , enables a passive global adversary to accurately infer the traffic pattern in an anonymous MANET without compromising any node. TP-DS works well on existing on-demand anonymous MANET routing protocols to determine the source node, destination node and the end-to-end communication path. Detailed simulations show that TP-DS can infer the hidden traffic pattern with accuracy as high than the TP-DS and gives the result with accuracy of 95%. DOI: 10.17762/ijritcc2321-8169.150310