DESIGN AND CONSTRUCTION OF HYBRID RENEWABLE ENERGY SYSTEM USING FOOD AND ANIMAL WASTE

ABSTRACT This study presents the design, implementation, and performance analysis of a cost-effective microcontroller-based data acquisition system (DAS) for precise temperature monitoring. Utilizing the AT89C52 microcontroller as the core processing unit and LM35 precision temperature sensors, the system addresses critical limitations in traditional methods, including inaccuracy, high cost, and lack of portability. The modular architecture integrates signal conditioning circuits, The hardware design emphasizes reliability and efficiency, featuring a robust regulated power supply unit, careful sensor interfacing with signal conditioning to minimize noise, and a firmware program developed in assembly language for optimal response time. The system acquires temperature data from multiple LM35 sensors, which provide a linear output of 10mV/°C across a range of -55°C to +150°C. The analog signals are conditioned, multiplexed, and converted to digital values by the 8-bit ADC before being processed by the microcontroller. Calibration routines are implemented to compensate for offset, gain, and nonlinearity errors, enhancing measurement accuracy. Performance evaluation focused on key metrics including accuracy, response time, power efficiency, and system reliability. Empirical testing involved comparing the system's temperature readings against known references and commercial benchmarks under various conditions. The analysis assessed the impact of factors such as ADC resolution (8-bit, ~1°C temperature resolution), signal conditioning effectiveness, multiplexer switching speed, and microcontroller processing latency on overall system performance. The study also examined power consumption characteristics and the system's resilience to environmental fluctuations. The developed microcontroller-based DAS demonstrates significant potential as an affordable, portable, and reliable solution for temperature monitoring, particularly in resource-constrained environments like developing regions. Its performance, while not matching high-end commercial systems in absolute precision, offers a viable and accessible alternative for applications where cost-effectiveness and local implementation are paramount, such as in healthcare incubators, poultry farms, and small-scale industrial processes. This work contributes to the advancement of indigenous technological capabilities and provides a foundation for future optimization and broader deployment of embedded data acquisition systems addressing local needs.