Alan McGibney

A wireless sensor network design tool to support building energy management

The physical location of sensor nodes strongly influences the performance of the network from the perspective of accurate data sensing and reliable communication. Therefore deployment planning can be regarded as an essential stepping stone to producing a viable network infrastructure. The research presented in this paper aims to assist the deployment of a Building Management System relying on wireless sensors and actuators. This is accomplished by the development of a WSN design and optimization software tool to support designers and system integrators when undertaking the difficult task of WSN deployment for building energy management.

Influence of people shadowing on optimal deployment of WLAN access points

With their low cost and high-speed data rate capabilities, installations of IEEE 802.11-based wireless local area networks (WLANs) are growing exponentially. Although many organizations have started using WLANs, there are still very few tools available that can help the design of WLAN networks. As a result, the current deployment remains ad-hoc in nature. The objective of this work is to develop modeling tools for performance optimization of WLAN networks and WLAN access points. In particular, propagation models are available that can predict the signal strength and interference in a WLAN system by taking into account environment specific parameters such as the structure of the building, presence or absence of stationary obstacles etc. This paper investigates the influence of moving obstacles, such as people, on radio wave propagation inside a building and the effect on received signal quality in a WLAN. Our findings suggest that the presence of moving obstacles seriously affects the performance of the system by introducing heavy variations in the received signal strength.

Design and deployment tool for in-building wireless sensor networks: A performance discussion

The design and deployment of a wireless sensor network (WSN) for building automation applications is a complex operation that requires expert knowledge and experience. This paper presents an evaluation of a WSN deployment support framework for in-building wireless infrastructures. A case study consisting of a sample network deployment for environmental monitoring is used to investigate the need for such support tools. The network infrastructure design suggested by the deployment support tool is compared against designs done using basic planning guidelines and a design based on an extensive site survey and experience. It will be shown how the deployment support tools provide a WSN with a reduced infrastructure cost and improved sensing packet delivery ratio when compared to the designs using traditional approaches.

Influence of people shadowing on bit error rate of IEEE802.11 2.4 GHz channel

Installations of IEEE 802.11-based wireless local area networks (WLANs) have been growing exponentially over the past two years due to their low cost and high-speed data rate capabilities. Although many organizations have started using WLANs, there are still few tools available that assist in the design of WLAN networks. As a result, the current deployment of WLAN networks remains ad-hoc in nature. The objective of the research reported here is to develop modeling tools for performance optimization of WLAN networks. In particular, we attempt to develop propagation models that can predict the signal strength and interference in a WLAN system by taking environment specific parameters into account such as the structure of the building, presence or absence of stationary obstacles, etc (COST231 Final Report, 1998). This paper investigates the influence of moving obstacles, such as people, on radio wave propagation inside a building and the effect on received signal quality, in particular the bit error rate in an IEEE802.11 2.4 GHz channel. Our findings suggest that the presence of moving obstacles, such as people, causes strong variations in the received signal, which seriously affects the quality of the received signal.

Managing wireless sensor networks within IoT ecosystems

Within the context of Internet of Things there is an expectation that devices will always be connected and an assumption that data will always be available, however there is little concern for the physical devices producing these data streams. There is a need to balance the appetite for data with the constraints and capabilities of the supporting physical infrastructure. This paper presents a management framework for wireless sensor networks within IoT ecosystems. This framework through cooperation and negotiation can lead to the creation of multiple virtual networks deployed over the same physical infrastructure to share resources, context, insight etc., in order to meet dynamic service requirements. This necessitates a shift from traditional management approaches focused on centralized management for bespoke solutions to the development of novel approaches for autonomous management via distributed intelligent gateways that proactively monitor and manage IoT WSN infrastructures to support multiple application verticals.

Wi-Design: A modelling and optimization tool for wireless embedded systems in buildings

As wireless embedded systems become more and more common and used across many application domains there is a need for modeling and design tools to support the deployment process. Although a significant amount of research has been carried out in the area of protocol design, middleware and energy, packaging and embedded systems design, there remains a lack of support tools for designers and system integrators when deploying complex indoor wireless infrastructures (Wi) to support site specific applications. In this paper we present a modeling tool known as Wi-Design that was developed to provide deployment support for engineers and system integrators when planning a wireless sensor infrastructure with particular focus on in building wireless applications. We show how the tool can simplify the deployment process and provide enhanced confidence in wireless deployments.

Predicting the expected accuracy for fingerprinting based WiFi localisation systems

WiFi localisation has become very popular in recent years. Most widely used are fingerprinting based techniques where a map of received signal strengths is used to infer the position based on comparing the current signal strength measurement to this map. Most research focuses on this inference itself and on the creation of accurate fingerprinting maps. In this paper we will not address those issues in depth but focus on analysing the fingerprint maps themselves in more detail. By looking closely into the maximum likelihood estimation for the position we will derive its expected uncertainty and show that it can be calculated for every possible position in advance from the fingerprint maps alone. This allows to derive an expected localisation accuracy map of the environment that can be used to assess and optimise the WiFi design based on localisation accuracy needs rather than relying on given access point placements solely based on coverage or signal-to-noise criteria.

Architecture for self-organizing, co-operative and robust Building Automation Systems

This paper provides an overview of the architecture for self-organizing, co-operative and robust Building Automation Systems (BAS) proposed by the EC funded FP7 SCUBA1 project. We describe the current situation in monitoring and control systems and outline the typical stakeholders involved in the case of building automation systems. We derive seven typical use cases which will be demonstrated and evaluated on pilot sites. From these use cases the project designed an architecture relying on six main modules that realize the design, commissioning and operation of self-organizing, co-operative, robust BAS.

A systematic engineering tool chain approach for self-organizing building automation systems

There is a strong push towards smart buildings that aim to achieve comfort, safety and energy efficiency, through building automation systems (BAS) that incorporate multiple subsystems such as heating and air-conditioning, lighting, access control etc. The design, commissioning and operation of BAS is already challenging when handling an individual subsystem; however when introducing co-operation between systems the complexity increases dramatically. Balancing the contradictory requirements of comfort, safety and energy efficiency and coping with the dynamics of constantly changing environmental conditions, usage patterns, user needs etc. is a demanding task. This paper outlines an approach to the systematic engineering of cooperating, adaptive building automation systems, which aims to formalize the engineering approach in the form of an integrated tool chain that supports the building stakeholders to produce site-specific robust and reliable building automation.

Tales from the C130 Horror Room: A Wireless Sensor Network Story in a Data Center

An important aspect of the management and control of modern data centers is cooling and energy optimization. Airflow and temperature measurements are key components for modeling and predicting environmental changes and cooling demands. For this, a wireless sensor network (WSN) can facilitate the sensor deployment and data collection in a changing environment. However, the challenging characteristics of these scenarios, e.g., temperature fluctuations, noise, and large amounts of metal surfaces and wiring, make it difficult to predict network behavior and therefore network planning and deployment. In this paper we report a 17-month long deployment of 30 wireless sensor nodes in a small data center room, where temperature, humidity and airflow were collected, along with RSSI, LQI, and battery voltage. After an initial unreliable period, a connectivity assessment performed on the network revealed a high noise floor in some of the nodes, which together with a default low CCA threshold triggered no packet transmissions, yielding a low PDR for those nodes. Increasing the CCA setting and relocating the sink allowed the network to achieve a reliability of 99.2% for the last eight months of the deployment, therefore complying with the project requirements. This highlights the necessity of using proper tools and dependable protocols, and defining design methodologies for managing and deploying WSNs in real-world environments.