It is well known that biology-inspired self-maintaining algorithms in wireless sensor nodes achieve near optimum time division multiple access (TDMA) characteristics in a decentralized manner and with very low complexity. We extend such distributed TDMA approaches to multiple channels (frequencies). This is achieved by extending the concept of collaborative reactive listening in order to balance the number of nodes in all available channels. We prove the stability of the new protocol and estimate the delay until the balanced system state is reached. Our approach is benchmarked against single-channel distributed TDMA and channel hopping approaches using TinyOS imote2 wireless sensors.

In this paper, we demonstrate the realistic test of a 2.4 GHz multi-hop wireless network for mountainous forest and watercourse environments. A multi-hop network using IEEE 802.15.4 XBee3 micro-modules and a communication protocol among nodes were developed. A wireless node deployment solution was introduced for practical testing. The proposed system’s communication reliability was tested in two different scenarios: a mountainous forest with sloping areas and trees and a watercourse, which referred to environmental and flooding monitoring applications. Wireless network performances were evaluated through the received signal strength indicator (RSSI) level of each wireless link, a packet delivery ratio (PDR), as the successful rate of packet transmission, and the end-to-end delay (ETED) of all data packets from the transmitter to the receiver. The experimental results demonstrate the success of the multi-hop WSN deployment and communication in both scenarios, where the RSSI of each link was kept at the accepted level and the PDR achieved the highest result. Furthermore, as a real-time response, the data from the source could be sent to the sink with a small ETED.

Nowadays, various image-based methods have been used in the area of monitoring. Whereas the precision of detection objects and real-time processing are the key issues for many applications. Considering the limitation of the working environment, the higher correctness and faster operating time can guarantee the work efficiency. In this paper, the image-based methods have been studied to monitoring the state of the flood in the real-time system. The performance of each image processing technique has been evaluated based on accuracy and processing time. In the flood monitoring system, the variation of important parameters can cause the change of performance and the effect of the variable parameters has been demonstrated from the experiment results. After comparing to the other image-based techniques, canny edge detection presents the best one, which also has better repeatability with the source image from different locations. Consequently, the improved canny edge detection method has been proved that can work very well on the real hardware in the outdoor environment.

Wireless Body Area Networks (WBANs) are a collection of vital and electrical signals measured from various body parts to help analyze therapeutic approaches for patients using wireless data transmission. The significant data has to communicate with collision avoidance to obtain high throughput. In this paper, a hybrid MAC layer communication is implemented between CSMA/CA and TDMA. CSMA/CA communication has been introduced to manage the TDMA sequence of transmissions without a central node. The experimental results in this system implement real wireless devices, TelosB, with the IEEE 802.15.4 standard. We studied the convergence speed of transmission sequence allocation, which was measured in the CSMA/CA period. When the number of nodes is small, the convergence time is slower than a large number of nodes. However, the number of nodes does not affect the number of rounds entering the transmission period. This parameter has been evaluated for the network and energy efficiency in WBANs. Packet delivery ratio, packet numbers, and energy consumption are examined for the different priority-based nodes in the TDMA period. The energy consumption can reduce to 40% for no priority when compared with high priority in the case of a priority-based node.

Hand grip strength (HGS) is a well-known parameter of physical capability, clinical health status, and functional work performance. However, the scarcity of standardized, region-specific HGS data for Southeast Asian populations restricts the accuracy of health screening practices and the development of ergonomics and occupational safety guidelines. The aim of this study was to measure the dominant-hand HGS for healthy young adult women of Malaysia and Thailand, to compare the HGS of these two groups of women, and to investigate the relationship between age and anthropometric variables and the HGS. Researchers conducted a cross-sectional study involving 166 healthy women aged 20 to 39 years. This study recruited 92 participants from Malaysia and 74 from Thailand, primarily from university students and staff populations. Dominant-hand HGS was measured using a Jamar dynamometer (Sammons Preston, USA) while participants adopted a standardized standing position with the forearm in a neutral posture. Thai women demonstrated significantly greater mean HGS than Malaysian women (27.31 ± 6.96 kg vs. 23.64 ± 4.67 kg; p < 0.001), corresponding to an approximately 16% difference and a medium-to-large effect size (Cohen’s d = 0.63). Among Thai participants, HGS was significantly associated with palm circumference (r = 0.544), height, weight, and age. These variables collectively explained 44.8% of the variation in HGS. In contrast, only height showed a modest association with HGS among Malaysian participants. Meanwhile, the corresponding regression model demonstrated limited explanatory capability. These findings reveal population-specific differences in both HGS and its anthropometric correlates when assessed under standardized testing conditions. The study provides protocol-specific, preliminary reference data for healthy young adult Malaysian and Thai women, which may inform future development of validated, population-specific reference standards. By generating population-specific reference data, this study contributes to improving the accuracy and equity of health monitoring practices, in line with the objectives of United Nations SDG 3 (Good Health and Well-being).