Department Publications

The DV-Hop algorithm is an attractive option for the localization of nodes in a wireless sensor network due to its simplicity. However it suffers from poor accuracy. This paper presents a novel algorithm to enhance the accuracy of this algorithm. The idea is to use the DV-Hop algorithm to estimate positions of the anchors which are already known. The estimation errors so obtained are then minimized through an optimization algorithm which finds the optimum correction to the hop size. The locations of the unknown nodes are then estimated with the modified hop size using least squares estimation. We examine the performance of the algorithm for varying node numbers, anchor ratios and radio range. The results show that the proposed algorithm has better performances in localization precision and stability than the original DV-Hop algorithm.

A novel wireless sensor network architecture designed for gathering and managing onsite dynamic information in emergency situations is presented. The system can operate in two different states-normal and emergency, where switching between states occurs according to perception from the environment. The main functionalities of the system include perceiving, processing and sharing the gathered information within a wireless sensor network which is deployed in a multi-story indoor environment. Algorithms for sensor localization, network self-configuration as well as data filtering and prediction are studied in the characterized emergency environment. The proposed architecture will act to reduce risk in rescue operations following an emergency as well as generating early warnings of possible emergencies.

The Australian construction industry is identified as one among five industries to receive priority attention under the Australian Work Health and Safety Strategy 2012-2022. Among the recorded construction fatalities in 2012, vehicle incidents accounted for 15% and being hit by moving objects accounted for 10%. Tracking of individuals on-site could provide a technological solution to improve safety. This paper proposes a novel, non-tagging-based, wireless networking solution (called device-free localization) to enhance safety on site. Device free localization techniques use radio signal propagation effects such as multi-path fading and shadowing caused by the obstruction(s). The proposed solution defines zones in the construction site. Zone identification is based on the risk associated with the location map of the site. Defining risk profiles considers the activities associated with the geographic location, such as …

Device free detection and localization is a promising and a very practical research area where installation of expensive sensors and/or tagging the intruder is not feasible. This paper reports a mesh network developed for device free trespasser detection. We use the Received Signal Strength Indicator (RSSI) measurements of the wireless links within the mesh as the sole sensing mechanism. A fingerprint of RSSI measurements characterizes the environment under normal conditions including multi-path effects. A technique to differentiate RSSI variations due to trespassers from those due to multi-path effects is demonstrated. The results of the experiments conducted in an outdoor environment have verified that the proposed method can be used to detect trespassers successfully. The reliability of the detection is improved by cross-correlating RSSI variations among the multiple links in the mesh. The ability to extend …

Transferring computational tasks from user-worn devices to everyday objects allows users to freely focus on their regular non-computing tasks. Identifying micro-activities (short-repetitive-activities that compose the macro-level behavior) enables the understanding of subtle behavioral changes and providing just-in-time information without explicit user input. In this paper, we propose the concept of micro-activity recognition of augmented-everyday-objects and evaluate the applicability of machine learning algorithms that are previously used for macro-level activity recognition. We outline a few proof-of-concept application scenarios that provide micro-activity-aware just-in-time information.

Localization is a significant consideration in a Wireless Sensor Network (WSN), as it is essential to correlate sensor information with the geographic location it originates from. The DV-Hop algorithm, being a range-free, distributed algorithm, is an attractive option in this regard, due to its simplicity. In this paper, we present two algorithms to improve the localization accuracy of the DV-Hop algorithm. The Hop Size derived through a distributed fashion by the DV-Hop algorithm is optimized using the knowledge of the position of the anchor nodes. The locations of the unknown nodes are then estimated using the optimum hop size. We examine the performance of the proposed algorithms through simulations in environments with varying node numbers, anchor ratios and radio range. The results show that the proposed algorithms have improved performance in localization accuracy and stability compared to the original …