Towards Optimal Deployment of a Sensor Network in a 3D Indoor Environment for the Mobility of People with Disabilities (Short Paper)

Mobility of people with disabilities is one of the most important challenges for their social integration. There have been significant effort to develop assistive technologies to guide the PWD during their mobility in recent years. However, these technologies have limitations when it comes to the navigation and guidance of these people through accessible routes. This is specifically problematic in indoor environments where detection, location and tracking of people, and other dynamic objects that may limit the mobility of these people, are very challenging. Thus, many researches have leveraged the use of sensors to track users and dynamic objects in indoor environments. However, in most of the described methods, the sensors are manually deployed. Due to the complexity of indoor environments, the diversity of sensors and their sensing models, as well as the diversity of the profiles of people with disabilities and their needs during their mobility, the optimal deployment of a sensor network is a challenging task. There exist several optimization methods to maximize coverage and minimize the number of sensors while maintaining the minimum connectivity between the sensor nodes in a network. Most of the current sensor network optimization methods oversimplify the environment and do not consider the complexity of 3D indoor environments. In this paper, we propose a novel 3D local optimization algorithm based on a geometric spatial data structure that takes into account some of these complexities for the purpose of helping PWD in their mobility in 3D indoor environments such as shopping centers, museums and other public buildings

Coverage and Energy Analysis of Mobile Sensor Nodes in Obstructed Noisy Indoor Environment: A Voronoi Approach

The rapid deployment of wireless sensor network (WSN) poses the challenge of finding optimal locations for the network nodes, especially so in (i) unknown and (ii) obstacle-rich environments. This paper addresses this challenge with BISON (Bio-Inspired Self-Organizing Network), a variant of the Voronoi algorithm. In line with the scenario challenges, BISON nodes are restricted to (i) locally sensed as well as (ii) noisy information on the basis of which they move, avoid obstacles and connect with neighboring nodes. Performance is measured as (i) the percentage of area covered, (ii) the total distance traveled by the nodes, (iii) the cumulative energy consumption and (iv) the uniformity of nodes distribution. Obstacle constellations and noise levels are studied systematically and a collision-free recovery strategy for failing nodes is proposed. Results obtained from extensive simulations show the algorithm outperforming previously reported approaches in both, convergence speed, as well as deployment cost.Comment: 17 pages, 24 figures, 1 tabl

Research on Wireless Multi-hop Networks: Current State and Challenges

Wireless multi-hop networks, in various forms and under various names, are being increasingly used in military and civilian applications. Studying connectivity and capacity of these networks is an important problem. The scaling behavior of connectivity and capacity when the network becomes sufficiently large is of particular interest. In this position paper, we briefly overview recent development and discuss research challenges and opportunities in the area, with a focus on the network connectivity.Comment: invited position paper to International Conference on Computing, Networking and Communications, Hawaii, USA, 201