Experimental Performance Comparison of a Modular Water-Based Photovoltaic–Thermal System Under Multiple Hydraulic Operating Modes in a Tropical Climate
In Brazil, more than 80% of households rely on electricity for water heating, representing approximately 13% of residential electricity consumption and significantly contributing to peak grid demand. As a prominent alternative for supplying household thermal energy and reducing grid stress, this study experimentally evaluates, under tropical climate conditions, the performance of a modular water-based photovoltaic–thermal (PVT) system and compares it with a conventional photovoltaic (PV) system operating simultaneously under identical environmental conditions. The PVT system, based on commercial PV modules coupled to roll-bond heat exchangers, a storage tank, and a shower outlet, was tested under three hydraulic regimes: natural thermosiphon, closed-loop, and Forced circulation. A dedicated ESP32-based data acquisition system, integrated with a cloud platform, continuously monitors electrical, thermal, and meteorological variables. Results show that PVT modules exhibit a small electrical efficiency reduction due to increased cell temperatures, which is largely compensated by the simultaneous thermal generation, yielding overall efficiency gains of 74.04%, 76.53%, and 7.62% over the reference PV system for Normal, Forced, and Closed circulation, respectively. The comparative analysis identifies Forced-circulation scheduling and the matching between thermal generation and consumption as key factors for performance optimization. The findings provide practical guidelines for deploying PVT systems to replace electric showers in tropical regions, reducing residential electricity consumption and mitigating peak-demand stress on the grid.
Bridging Legacy Smart Meters to Modern IoT Networks Based on LoRaWAN
The integration of legacy energy meters into modern smart grids remains a challenge due to the unviable cost and logistical complexity of full-scale replacement. In Brazil, this problem is acute, with millions of meters operating on a sort of Protocol for Advanced Measurement Infrastructure (AMI) legacy called Protocolo para Infraestrutura de Medição Avançada (PIMA), provoking incompatibility with modern internet of things (IoT) networks and impeding the rollout of AMIs. This letter presents a novel low-power sensor interface platform designed to resolve physical-layer data acquisition barriers in legacy infrastructure. The system architecture addresses the specific sensing constraints of open-collector serial outputs, decoding proprietary PIMA frames with high precision and transmitting key measurements over long range wide area networks (LoRaWAN). An experimental validation confirmed the sensing accuracy, with a perfect match between transmitted data and the meter’s physical display. This retrofit solution provides a verified and viable pathway for the rapid, scalable, and economical integration of legacy assets into modern AMI, bypassing the need for costly meter replacement.
Dispersion turning point enhanced on-chip bimodal interferometry
A transverse-magnetic (TM) polarized strip bimodal waveguide (BiMW) sensor operating near a dispersion turning point (DTP) is proposed and experimentally demonstrated on a silicon-on-insulator platform. To enhance the sensitivity of common-path BiMW sensors, near-DTP operation is realized by driving the modal group-index difference toward zero. By exploiting the intrinsic width-dependent dispersion of the TM modes, the DTP is achieved in a standard strip waveguide configuration through waveguide-width optimization, without complex dispersion-engineering structures. With a sensing length of only 0.8 mm, the sensor achieves a refractive-index sensitivity of 7456 nm/RIU and a limit of detection (LoD) of 1.57 × 10−6 RIU. This work provides a compact, fabrication-accessible, and experimentally validated approach for high-performance on-chip refractive-index sensing, with potential applications in biochemical sensing.
Characterization and functional evaluation of a fiber-optic instrumented impedance-controlled upper-limb exoskeleton
The use of active exoskeletons for musculoskeletal disorder (MSD) prevention is increasing in industrial environments. Wearable sensing technologies enable closed-loop control of these devices. However, magnetic disturbances and sensor fixation issues can compromise measurement reliability and affect exoskeleton behavior. Polymer optical fiber (POF) sensors offer intrinsic immunity to electromagnetic interference and mechanical compliance, making them a promising alternative for wearable kinematic sensing. Nevertheless, their integration within the control loop of active exoskeletons remains largely unexplored. This study investigates the impact of POF sensing modality integrated within the impedance control loop of an upper-limb exoskeleton, focusing on control performance and system dynamics. A two-stage experimental protocol was conducted under an approved ethical protocol. First, a test-bench evaluation showed that POF sensing modality achieves comparable rise time and mean absolute error to IMU sensing modality, though it resulted in a 0.565 s increase in settling time. Second, participants performed standardized lifting tasks under assisted (Exo-POF and Exo-IMU) and unassisted (No-Assist) conditions. Kinematic and electromyographic (EMG) data showed a 16–23% reduction in muscle activation while preserving range of motion. These findings demonstrate that POF sensing modality significantly influences system dynamics and human–robot interaction. Subsequently, the proof of concept suggests the feasibility of the proposed approach during lifting, handling, and lowering tasks, opening the way for future validation under representative industrial environments.