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@article{203097,
        author = {Prof. Vijaykumar Bhanuse and Shriyash Jadhav and Prajwal Kale and Mithil Ambhure and Tushar Khurale},
        title = {Design and Development of a Sensor Calibration and Error Analysis Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {9497-9506},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=203097},
        abstract = {Accurate sensor calibration is a fundamental prerequisite for reliable measurement in industrial instrumentation, process control, and quality assurance systems. This paper presents the design and development of a comprehensive hardware and software platform for sensor calibration and error analysis, targeting final-year engineering education and small-scale industrial calibration laboratories. The platform integrates an Arduino/ESP32-based data acquisition subsystem with analog signal conditioning circuits to collect raw sensor outputs from temperature, pressure, and load sensors. Collected data is processed using Python-based computational tools implementing linear regression, curve fitting, and statistical error analysis algorithms. The system computes and reports calibration curves, sensitivity coefficients, linearity errors, hysteresis errors, repeatability errors, and offset corrections. Compensation equations derived from the calibration process are stored and applied to correct subsequent sensor readings in real time. Experimental evaluation using the LM35 temperature sensor demonstrates a maximum calibration error reduction from ±2.5°C uncalibrated to ±0.3°C post-calibration. The platform is designed in alignment with ISO 17025 calibration laboratory standards and provides a practical, cost-effective tool for demonstrating industrial instrumentation concepts. Results confirm that systematic calibration with rigorous error analysis significantly improves sensor measurement accuracy, making the platform suitable for process industries, pharmaceutical applications, and educational instrumentation laboratories.},
        keywords = {Sensor Calibration, Error Analysis, Signal Conditioning, Linear Regression, Hysteresis, Repeatability, Linearity, Instrumentation, ISO 17025, Compensation Equation},
        month = {May},
        }