Smart One-Channel Sensor Node for Ambient Vibration Test with Applications to Structural Health Monitoring of Large Civil Infrastructures

Dynamic characteristics of structures have been monitored for safe operation and efficient maintenance of large civil infrastructures. For vibration data measurement, the conventional system uses cables, which cause very expensive costs and inconvenient installation. Therefore, various wireless sensor nodes have been developed to replace the conventional wired system. However, there still remain lots of issues to be resolved such as time synchronization between sensor nodes, data loss, data security, and power supply. In this study, Smart One-Channel Sensor Node (SOSN) was developed to measure vibration data, which can practically solve the issues on installation, time synchronization, and data storage. It is designed for temporal measurement with a limited capacity to operate for several hours using embedded batteries. Laboratory tests were carried out to verify the performance of the developed SOSN compared with conventional wired system. Its practical advantages were investigated through three full-scale tests on large civil infrastructures. Three field applications revealed that SOSN is a very practical tool for short-term monitoring of large civil infrastructures with respect to traffic control, installation time and convenience, secure data gathering, and so forth.open0

TDMA frame design for a prototype underwater RF

Very low frequency electromagnetic communication system is used in a small scale underwater wireless sensor network for coastal monitoring purposes, as recent research has demonstrated distinct advantages of radio waves compared to acoustic and optical waves in shallow water conditions. This paper describes the detailed TDMA and packet design process for the prototype sensor system. The lightweight protocol is time division based in order to fit the unique characteristics and specifications of the network. Evaluations are based on initial beach trial as well as modeling and simulations

Security and Privacy Issues in Wireless Sensor Networks for Healthcare Applications

The use of wireless sensor networks (WSN) in healthcare applications is growing in a fast pace. Numerous applications such as heart rate monitor, blood pressure monitor and endoscopic capsule are already in use. To address the growing use of sensor technology in this area, a new field known as wireless body area networks (WBAN or simply BAN) has emerged. As most devices and their applications are wireless in nature, security and privacy concerns are among major areas of concern. Due to direct involvement of humans also increases the sensitivity. Whether the data gathered from patients or individuals are obtained with the consent of the person or without it due to the need by the system, misuse or privacy concerns may restrict people from taking advantage of the full benefits from the system. People may not see these devices safe for daily use. There may also possibility of serious social unrest due to the fear that such devices may be used for monitoring and tracking individuals by government agencies or other private organizations. In this paper we discuss these issues and analyze in detail the problems and their possible measures

Artificial neural networks for wireless structural control

We live in an age when people desire taller buildings and longer bridges. These increasing demands of more flexible structures challenge civil engineers to ensure structural safety in the state where they are more prone to extreme dynamic loading, such as earthquakes. Extensive wiring required in traditional structural control applications may be expensive and inconvenient, especially for large scale structures. To improve the scalability, wireless sensors offer a promising alternative. However, the presence of time delay and data loss in a wireless sensor network can potentially reduce the performance of the control system. Here an artificial neural network is proposed to improve the performance of a wireless sensor network based control system. The proposed technique is named as Neural Network Wireless Correction Function (NNWCF). By applying this strategy, a wireless structural control can be utilized without experiencing major performance degradation due to the wireless characteristics

Telemedicine Programs in Respiratory Diseases

Telemedicine programs are widely used in respiratory diseases, more often in patients with chronic obstructive pulmonary diseases (COPD). Telemedicine platforms use several devices to measure vital signs such as heart rate, respiratory rate, pulsioximetry or blood pressure between others. It is not unusual that patients could do questionnaires about clinical situation or communicate with their nurses via telephone, video-calling and/or Skype. The majority of results has been positive, with reduction in the number of emergency visits, hospitalizations and noninvasive ventilations. Despite their promising results, telemedicine programs/platforms are slow to implement. In this chapter, we reviewed some of the factors related to telemedicine implementation such as patients’ adherence, impact of telemedicine design and professionals\u27 resistance to change between others

Passive Radar for Opportunistic Monitoring in e-Health Applications

This paper proposes a passive Doppler radar as a non-contact sensing method to capture human body movements, recognize respiration, and physical activities in e-Health applications. The system uses existing in-home wireless signal as the source to interpret human activity. This paper shows that passive radar is a novel solution for multiple healthcare applications which complements traditional smart home sensor systems. An innovative two-stage signal processing framework is outlined to enable the multi-purpose monitoring function. The first stage is to obtain premier Doppler information by using the high speed passive radar signal processing. The second stage is the functional signal processing including micro Doppler extraction for breathing detection and support vector machine classifier for physical activity recognition. The experimental results show that the proposed system provides adequate performance for both purposes, and prove that non-contact passive Doppler radar is a complementary technology to meet the challenges of future healthcare applications