Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any "thing" we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring application

Supporting Cyber-Physical Systems with Wireless Sensor Networks: An Outlook of Software and Services

Sensing, communication, computation and control technologies are the essential building blocks of a cyber-physical system (CPS). Wireless sensor networks (WSNs) are a way to support CPS as they provide fine-grained spatial-temporal sensing, communication and computation at a low premium of cost and power. In this article, we explore the fundamental concepts guiding the design and implementation of WSNs. We report the latest developments in WSN software and services for meeting existing requirements and newer demands; particularly in the areas of: operating system, simulator and emulator, programming abstraction, virtualization, IP-based communication and security, time and location, and network monitoring and management. We also reflect on the ongoing efforts in providing dependable assurances for WSN-driven CPS. Finally, we report on its applicability with a case-study on smart buildings

7. GI/ITG KuVS Fachgespräch Drahtlose Sensornetze

In dem vorliegenden Tagungsband sind die Beiträge des Fachgesprächs Drahtlose Sensornetze 2008 zusammengefasst. Ziel dieses Fachgesprächs ist es, Wissenschaftlerinnen und Wissenschaftler aus diesem Gebiet die Möglichkeit zu einem informellen Austausch zu geben – wobei immer auch Teilnehmer aus der Industrieforschung willkommen sind, die auch in diesem Jahr wieder teilnehmen.Das Fachgespräch ist eine betont informelle Veranstaltung der GI/ITG-Fachgruppe „Kommunikation und Verteilte Systeme“ (www.kuvs.de). Es ist ausdrücklich keine weitere Konferenz mit ihrem großen Overhead und der Anforderung, fertige und möglichst „wasserdichte“ Ergebnisse zu präsentieren, sondern es dient auch ganz explizit dazu, mit Neueinsteigern auf der Suche nach ihrem Thema zu diskutieren und herauszufinden, wo die Herausforderungen an die zukünftige Forschung überhaupt liegen.Das Fachgespräch Drahtlose Sensornetze 2008 findet in Berlin statt, in den Räumen der Freien Universität Berlin, aber in Kooperation mit der ScatterWeb GmbH. Auch dies ein Novum, es zeigt, dass das Fachgespräch doch deutlich mehr als nur ein nettes Beisammensein unter einem Motto ist.Für die Organisation des Rahmens und der Abendveranstaltung gebührt Dank den beiden Mitgliedern im Organisationskomitee, Kirsten Terfloth und Georg Wittenburg, aber auch Stefanie Bahe, welche die redaktionelle Betreuung des Tagungsbands übernommen hat, vielen anderen Mitgliedern der AG Technische Informatik der FU Berlin und natürlich auch ihrem Leiter, Prof. Jochen Schiller

Generic sensor network architecture for wireless automation (GENSEN)

fi=vertaisarvioimaton|en=nonPeerReviewed

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Wireless data management system for environmental monitoring in livestock buildings

The impact of air quality on the health, welfare and productivity of livestock needs to be considered, especially when livestock are kept in enclosed buildings. The monitoring of such environmental factors allows for the development of appropriate strategies to reduce detrimental effects of sub-optimal air quality on the respiratory health of both livestock and farmers. In 2009, an environmental monitoring system was designed, developed and tested that allowed for the monitoring of a number of airborne pollutants. One limitation of the system was the manual collection of logged data from each unit. This paper identifies limitations of the current environmental monitoring system and suggests a range of networking technologies that can be used to increase usability. Consideration is taken for the networking of environmental monitoring units, as well as the collection of recorded data. Furthermore, the design and development of a software system that is used to collate and store recorded environmental data from multiple farms is explored. In order to design such a system, simplified software engineering processes and methodologies have been utilised. The main steps taken in order to complete the project were requirements elicitation with clients, requirements analysis, system design, implementation and finally testing. The outcome of the project provided a potential prototype for improving the environmental monitoring system and analysis informing the benefit of the implementation

FUZZY BASED SECURITY ALGORITHM FOR WIRELESS SENSOR NETWORKS IN THE INTERNET OF THINGS PARADIGM

Published ThesisThe world is embracing the idea of Internet of Things and Industrial Revolution 4.0. However, this acceptance of computerised evolution is met with a myriad of challenges, where consumers of this technology are also growing ever so anxious about the security of their personal data as well as reliability of data collected by the millions and even billions of sensors surrounding them. Wireless sensor networks are the main baseline technology driving Internet of things; by their very inherent nature, these networks are too vulnerable to attacks and yet the network security tools designed for conventional computer networks are not effective in countering these attacks. Wireless sensors have low computational resources, may be highly mobile and in most cases, these networks do not have a central point which can be marked as an authentication point for the sensors, any node can join or leave whenever they want. This leaves the sensors and the internet of things applications depending on them highly susceptible to attacks, which may compromise consumer information and leave security breaches in situation that need absolute security such as homes or even the cars they drive. There are many possibilities of things that could go wrong when hackers gain control of sensors in a car or a house. There have been many solutions offered to address security of Wireless Sensor Networks; however, most of those solutions are often not customised for African context. Given that most African countries have not kept pace with the development of these underlying technologies, blanket adoption of the solutions developed for consumption in the developed world has not yielded optimal results. The focus of this research was the development of an Intrusion Detection System that works in a hierarchical network structured Wireless Sensor Network, where cluster heads oversee groups of nodes and relay their data packets all the way to the sink node. This is a reactive Intrusion Detection System (IDS) that makes use of a fuzzy logic based algorithm for verification of intrusion detections. This system borrows characteristics of traditional Wireless Sensor Networks in that it is hosted external to the nodes; that is, on a computer or server connected to the sink node. The rational for this is the premise that developing the system in this manner optimises the power and processing resource of nodes because no part of the IDS is found in the nodes and they are left to focus purely on sensing. The Intrusion Detection System makes use of remote Over The Air programming to communicate with compromised nodes, to either shut down or reboot and is designed with the ZigBee protocol in mind. Additionally, this Intrusion Detection System is intended to being part of a larger Internet of Things integration framework being proposed at the Central University of Technology. This framework is aimed at developing an Internet of Things adoption strategy customised for African needs and regionally local consumers. To evaluate the effectiveness of the solution, the rate of false detections being picked out by the security algorithm were reduced through the use of fuzzy logic systems; this resulted in an accuracies of above 90 %. The algorithm is also very light when asymptotic notation is applied, making it ideal for Wireless Sensors. Lastly, we also put forward the Xbee version of the Triple Modular Redundancy architecture, customised for Wireless sensor networks in order to beef-up on the security solution presented in this dissertation

Energy efficiency in data collection wireless sensor networks

This dissertation studies the problem of energy efficiency in resource constrained and heterogeneous wireless sensor networks (WSNs) for data collection applications in real-world scenarios. The problem is addressed from three different perspectives: network routing, node energy profiles, and network management. First, the energy efficiency in a WSN is formulated as a load balancing problem, where the routing layer can diagnose and exploit the WSN topology redundancy to reduce the data traffic processed in critical nodes, independent of their hardware platform, improving their energy consumption and extending the network lifetime. We propose a new routing strategy that extends traditional cost-based routing protocols and improves their energy efficiency, while maintaining high reliability. The evaluation of our approach shows a reduction in the energy consumption of the routing layer in the busiest nodes ranging from 11% to 59%, while maintaining over 99% reliability in WSN data collection applications. Second, a study of the effect of the MAC layer on the network energy efficiency is performed based on the nodes energy consumption profile. The resulting energy profiles reveal significant differences in the energy consumption of WSN nodes depending on their external sensors, as well as their sensitivity to changes in network traffic dynamics. Finally, the design of a general integrated framework and data management system for heterogeneous WSNs is presented. This framework not only allows external users to collect data, while monitoring the network performance and energy consumption, but also enables our proposed network redundancy diagnosis and energy profile calculations