Water is one of the most precious resources. However, industrial development has made water pollution a critical problem today and thus water quality monitoring and surface cleaning are essential for water resource protection. In this study, we have used the sensor fusion technology as a basis to develop a multi-function unmanned surface vehicle (MF-USV) for obstacle avoidance, water-quality monitoring, and water surface cleaning. The MF-USV comprises a USV control unit, a locomotion module, a positioning module, an obstacle avoidance module, a water quality monitoring system, a water surface cleaning system, a communication module, a power module, and a remote human–machine interface. We equip the MF-USV with the following functions: (1) autonomous obstacle detection, avoidance, and navigation positioning, (2) water quality monitoring, sampling, and positioning, (3) water surface detection and cleaning, and (4) remote navigation control and real-time information display. The experimental results verified that when the floating garbage located in the visual angle ranged from −30° to 30° on the front of the MF-USV and the distances between the floating garbage and the MF-USV were 40 and 70 cm, the success rates of floating garbage detection are all 100%. When the distance between the floating garbage and the MF-USV was 130 cm and the floating garbage was located on the left side (15°~30°), left front side (0°~15°), front side (0°), right front side (0°~15°), and the right side (15°~30°), the success rates of the floating garbage collection were 70%, 92%, 95%, 95%, and 75%, respectively. Finally, the experimental results also verified that the applications of the MF-USV and relevant algorithms to obstacle avoidance, water quality monitoring, and water surface cleaning were effective.

A novel optical fiber array-type of sensing instrument with temperature compensation for real-time detection was developed to measure oxygen, carbon dioxide, and ammonia simultaneously. The proposed instrument is multi-sensing array integrated with real-time measurement module for portable applications. The sensing optical fibers were etched and polished before coating to increase sensitivities. The ammonia and temperature sensors were each composed of a dye-coated single-mode fiber with constructing a fiber Bragg grating and a long-period filter grating for detecting light intensity. Both carbon dioxide and oxygen sensing structures use multimode fibers where 1-hydroxy-3,6,8-pyrene trisulfonic acid trisodium salt is coated for carbon dioxide sensing and Tris(2,2′-bipyridyl) dichlororuthenium(II) hexahydrate and Tris(bipyridine)ruthenium(II) chloride are coated for oxygen sensing. Gas-induced fluorescent light intensity variation was applied to detect gas concentration. The portable gas sensing array was set up by integrating with photo-electronic measurement modules and a human-machine interface to detect gases in real time. The measured data have been processed using piecewise-linear method. The sensitivity of the oxygen sensor were 1.54%/V and 9.62%/V for concentrations less than 1.5% and for concentrations between 1.5% and 6%, respectively. The sensitivity of the carbon dioxide sensor were 8.33%/V and 9.62%/V for concentrations less than 2% and for concentrations between 2% and 5%, respectively. For the ammonia sensor, the sensitivity was 27.78%/V, while ammonia concentration was less than 2%.

A major cause of high energy consumption for air conditioning in indoor spaces is the thermal storage characteristics of a building’s envelope concrete material; therefore, the physiological signals (temperature and humidity) within concrete structures are an important reference for building energy management. The current approach to measuring temperature and humidity within concrete structures (i.e., thermocouples and fiber optics) is limited by problems of wiring requirements, discontinuous monitoring, and high costs. This study uses radio frequency integrated circuits (RFIC) combined with temperature and humidity sensors (T/H sensors) for the design of a smart temperature and humidity information material (STHIM) that automatically, regularly, and continuously converts temperature and humidity signals within concrete and transmits them by radio frequency (RF) to the Building Physiology Information System (BPIS). This provides a new approach to measurement that incorporates direct measurement, wireless communication, and real-time continuous monitoring to assist building designers and users in making energy management decisions and judgments.

Tiles are commonly used to cover the exteriors of buildings in Taiwan. However, older buildings in Taiwan encounter the problem of tiles falling off due to natural deterioration, which is unsightly, and more importantly, a threat to public safety. Nevertheless, no current method exists that can effectively detect flaws in building tiles in real time. This study combined the fields of civil engineering and automatic control to reduce risks caused by falling tiles by improving real-time detection of at-risk areas. Micro-resistance was combined with fuzzy theory as the logical foundation for evaluating tile status. String-type strain gauges were adopted as sensors to design a smart skin sensory system that could measure signs of deterioration in tile surface lesions. The design was found to be feasible. In the future, it can be further developed for facile real-time assessment of tile status.

The health of human bodies can be determined by physiological signs; similarly, the physiological signs displayed by a building's reinforced concrete (RC) structure (temperature and humidity) are of the same importance to building health management. This study evaluates building health by integrating a low-cost radio frequency integrated circuit (RFIC) with temperature/humidity sensor chips. Concrete inner temperature and humidity data are sent back to the building physiology information system (BPIS) via radio frequency (RF) wireless transmission automatically, regularly and continuously to provide a reference to on-site building managers during health diagnosis and analysis of building structures.