Lifetime is one of the most critical indexes of the Wireless Sensor Network (WSN). In this paper, we propose a clustering protocol based on the meta-heuristic approach (CPMA). CPMA takes the network lifetime as the primary consideration and consists of two parts. The first part focuses on the online cluster head selection and network communication coordination. The selection is based on the Harmony Search (HS) Algorithm, which aims to reduce the total energy dissipation and smooth the energy distribution throughout the network. Currently, most clustering protocols cannot automatically tune the corresponding protocol parameters according to the diversity of different WSNs. To solve such issue, the second part of CPMA uses the Artificial Bee Colony (ABC) algorithm to optimize its crucial parameters. The optimization is offline and will be executed only once before the network is working. We make a detailed comparison of CPMA with classical clustering protocols. The results show that CPMA can better prolong the network lifetime and improve network throughput under almost all the network conditions. Furthermore, our simulation also exhibits that CPMA has good adaptability and performs well under different network lifetime definitions. All the results prove that CPMA has the advantages of being suitable and efficient for a wide number of WSN applications.

With the continuous advancement of the “dual-carbon” strategy, the penetration of renewable energy sources such as wind and photovoltaic (PV) power has steadily increased, imposing more stringent requirements on the safe and stable operation of modern power systems. As the core components of these systems, critical electrical devices operate under harsh conditions characterized by high voltage, strong electromagnetic interference (EMI), and confined high-temperature environments. Their operating status directly affects the reliability of the power supply, and any fault may trigger cascading failures, resulting in significant economic losses. To address the issues of low inspection efficiency, limited fault-identification accuracy, and unstable data transmission in strong-EMI environments, this study proposes an intelligent inspection system for power equipment based on multi-technology integration. The system incorporates a redundant dual-mode wireless transmission architecture combining Wireless Fidelity (Wi-Fi) and Fourth Generation (4G) cellular communication, ensuring reliable data transfer through adaptive link switching and anti-interference optimization. A You Only Look Once version 8 (YOLOv8) object-detection algorithm integrated with Open Source Computer Vision (OpenCV) techniques enables precise visual fault identification. Furthermore, a multi-source data-fusion strategy enhances diagnostic accuracy, while a dedicated monitoring scheme is developed for the water-cooling subsystem to simultaneously assess cooling performance and fault conditions. Experimental validation demonstrates that the proposed system achieves a fault-diagnosis accuracy exceeding 95.5%, effectively meeting the requirements of intelligent inspection in modern power systems and providing robust technical support for the operation and maintenance of critical electrical equipment.

How to obtain the information from massive tags is a key focus of RFID applications. The occurrence of collisions leads to problems such as reduced identification efficiency in RFID networks. To tackle such challenges, most tag collision arbitration protocols focus on scheduling tag identification with collision avoidance. However, how to effectively identify tags in collisions to improve identification efficiency has not been well explored. In this paper, we propose a group query allocation method to divide the string space into mutually disjoint subsets which contains several strings. Each string can be viewed as a full ID or partial ID of a tag. When multiple string from a subset are sent simultaneously, the reader can identify all of them in a time slot. Based on the group query allocation method, a segment detection based characteristic group query tree (SD-CGQT) protocol is presented for fast tag identification by significantly reducing the collision slots and transmitted bits. Numerous experimental results verify the superiority of the proposed SD-CGQT, compared to prior arts in system efficiency, total identification time, communication complexity and energy consumption.

The monitoring of magnetic fields is extremely important in many industrial environments, e.g., power grids. Despite of its importance, the existing monitoring methods either are large in size, require high power consumptions and manual observation, or although integrated in small wireless devices, need the use of batteries, increasing maintenance costs. This paper proposes an intermittent magnetic field monitoring system based on passive ultra-high frequency (UHF) radio frequency identification (RFID) technology. A magnetic field magnitude sensor has been integrated into a micro-controller unit (MCU) based tag, and the standard RFID communication protocol ISO/IEC 18000-6 Type C has been partially modified to allow faster sensed data transfer, especially for multiple tag situations rarely considered in the open literature. Static or 50 Hz magnetic field sensing accuracy lower than 3% have been experimentally measured with reasonable tag charging times and read distances, making possible for example to monitor magnetic fields on more than 10 locations simultaneously with a 60 s of updating time with a tag read range of 3 m.

An ultrahigh-frequency (UHF) radio frequency identification (RFID) tag structure which includes both received signal demodulation and reflected signal amplification abilities for standard compatibility is described in this letter. To let demodulation and reflected signal amplification features coexist, a simple RF switch is used to separate the reception and reflection signal paths, and a reflection amplifier (RA) is connected to one of the two RF switch paths to realize the amplified reflection state. The RF switch can guarantee good impedance matching under reception/reflection conditions; moreover, by selecting it judiciously, i.e., with a low insertion loss, it is possible to simultaneously achieve high tag sensitivity and reflection amplification. Measurement on a tag prototype has revealed a maximum read range of 96 m (with a tag sensitivity of $-$ 42 dBm) and an average power consumption of 1.134 mW.