Psychological disorders, including emotion and behavioral disorders, are common in the modern society. For example, previous studies by the New Zealand Mental Health Survey and the US National Co-morbidity Surveys (NCS), have found that the incidence of depression from ages 18 to 32 to be around 18%. Thus, there is a need to effectively monitor the emotional or affective states of these patients with psychological illness. Whilst real-time and continuous psychological monitoring systems are still not prevalent, the monitoring of physiological signals are made easier with mobile sensors that can be attached to the human body. These physiological signals can then be processed using an embedded processor to provide an alternative means for automatic emotion recognition. However, for such a system to be developed, the relationship between physiological and psychological signals has to be understood. This paper aims to address this by investigating the relationship between the emotional experiences from multiple subjects and their physiological responses, including the skin conductance, heart rate, respiration and movements of the facial muscles. In summary, preliminary evaluations described in this paper demonstrated that the heart rate, respiration, blood volume pulse and electromyography signals have an impact on the recognition rate achievable by the proposed multi-user physiological response-based emotion detection system.

With the development of sensor and wireless communication technologies, the concept of body sensor networks (BSNs) is proposed in recent years. BSNs are used to measure a large number of vital signs of the human body. Body sensor devices are typically powered by batteries and difficult to replace, so energy efficient medium access control (MAC) protocols, which can perform medium access mechanism with less energy are necessary. In this paper, we propose a novel energy saving MAC protocol for mobile BSNs based on time division multiple access (TDMA). An uplink, downlink asymmetric network architecture is introduced. A changeable access and sleep frame format as well as a routing algorithm are proposed. Simulation results show that the proposed MAC protocol achieves lower energy consumption than IEEE 802.15.6.

In this paper, we explore the use of wireless mesh networks (WMN) for the purpose of exchanging GPS raw data within GPS stations in a WMN to support real-time in-network processing of low-cost single-frequency GPS devices. A proof of concept deployment with a small number of GPS stations was studied. This experiment validates the feasibility of using WMN to enable real-time in-network processing in a dense GPS network for deformation monitoring. The experimental results demonstrated a significant reduction in station location errors when differential epoch-by-epoch processing method is used and provides real-time relative location between stations in the network.

In this paper, we present an overview of a system that we are developing for the continuous monitoring of water distribution systems in Singapore. We discuss the design and implementation of the system that enables real-time detection of pipe burst events.

In this paper, the use of mesh networking for the Sumatran continuous-Global Positioning System array (SuGAr) was proposed to optimize the telemetry between the nodes in the array and a centralized remote data server. Currently, data from the array is transferred directly to the data server via dedicated satellite links from each node in the array. This requires each node to be connected to a satellite modem and is cost-ineffective as subscriptions for each link have to be maintained. In this paper, the use of long range multi-hop radios to establish mesh networks was proposed in order to reduce the number of satellite links required as well as to perform cluster-based compression to reduce the bandwidth requirements. Due to the geographical distances between the nodes and the limitations of the radio range, clusters of mesh networks will be formed and each cluster will require only a minimum of only one satellite link. Furthermore, rather than compressing the collected data separately at each GPS station, the cluster-heads can also perform compression on all the collected data within the cluster prior to transmission to the data server. Due to the inherent correlation between the data from the GPS stations, the compression of the larger dataset will reduce the total bandwidth required to transfer the observed data. To demonstrate the optimization achieved, actual GPS data collected from the SuGAr network from the last two months (61 days) of 2007 was used in the evaluation of the proposed solution and results showed that the proposed solution significant reduced the number of bytes transmitted to the data server via the satellite links.

This paper presents the results of experiments to compare the performance of energy-efficient SpeckMAC Medium Access Control (MAC) algorithms, SpeckMAC-D and SpeckMAC-B, with the Berkeley MAC for miniature resource-constrained mobile ad-hoc networks, such as Specknets. These MAC algorithms conserve energy by reducing the amount of idle-listening time during communications by periodic sampling of the radio channel. Previous work had compared the three algorithms on the ProSpeckz hardware in terms of the lifetime of the batteries powering the platform: SpeckMAC protocols achieved longer lifetimes compared to B-MAC, especially for batteries with smaller capacities. This paper presents further analysis of the performance of the MAC algorithms through experiments, on the Perspeckz-64, a test-bed of 64 ProSpeckz nodes, for power consumption of unicast and broadcast traffic, the delivery ratio. and one-hop and multi-hop latencies. The results demonstrated that the SpeckMAC algorithms outperformed B-MAC for all the metrics considered.

Speckled computing (Arvind, D.K. and Wong, K.J., Proc. IEEE Int. Symp. on Consumer Electronics, p.219-23, 2004) is an emerging technology in which data is sensed in minute (eventually one cubic millimetre) semiconductor grains called specks. Information is extracted in situ from each speck and is exchanged and processed in a collaborative fashion in a wireless network of thousands of specks, called a specknet. Specks are not assumed to be static, and therefore estimating and maintaining the logical location of the mobile specks in a network is essential for a number of speckled computing and sensor network applications. A novel lightweight distributed algorithm is introduced for this purpose and simulation results are presented to determine the goodness of the algorithm for different parameters, The algorithm was also successfully ported to a hardware prototype of the speck called the ProSpeckz. The problems and issues of porting the algorithm onto such a resource-constrained hardware platform are discussed. Finally, the paper concludes with plans to improve the algorithm.