Development of IoT-enabled Sensors for Real-Time Monitoring of Chemical Reactor Conditions

Thesis Abstract

The efficiency, safety, and sustainability of chemical manufacturing processes heavily rely on precise monitoring of reactor conditions, yet traditional sensor systems often face limitations in real-time data acquisition, resilience to harsh environments, and scalability. This study aims to develop an Internet of Things (IoT)-enabled sensor platform capable of providing continuous, real-time monitoring of critical parameters such as temperature, pressure, pH, and chemical composition within chemical reactors. The specific objectives include designing and prototyping IoT sensor nodes with integrated data acquisition and wireless communication capabilities, evaluating their performance under simulated reactor conditions, optimizing data transmission protocols for minimal latency and energy consumption, and establishing a predictive maintenance framework based on collected data. The research adopts a mixed-methods approach centered on experimental development complemented by analytical modeling. Quantitative data will be collected via laboratory experiments involving the deployment of prototype sensors within a controlled chemical reactor setup simulating industrial conditions. The study population comprises chemical reactor environments in laboratory settings, with a sample of 30 sensor nodes developed using Arduino-based microcontrollers, equipped with chemical-resistant sensors and Wi-Fi modules. Data collection instruments include custom-designed sensor modules, data logging software, and environmental simulation chambers. The reliability and validity of the sensor readings will be ensured through calibration against industry-standard reference instruments, such as thermocouples, pressure transducers, and spectrophotometers, with data analyzed using regression analysis to assess sensor accuracy, ANOVA for performance comparisons, and time-series analysis to evaluate data stability over prolonged periods. Key expected findings include the successful integration of IoT technology with chemical sensors to achieve high accuracy, low latency, and robust data transmission in environments with high temperature, pressure, and corrosive agents. It is anticipated that the developed sensor network will demonstrate a detection sensitivity of less than ±1% for chemical parameters and exhibit operational stability over a continuous 72-hour testing cycle. Additionally, the study expects to establish that optimized wireless protocols significantly reduce energy consumption by at least 25% compared to conventional IoT deployments, thereby enhancing device longevity and reliability. Analysis of the collected data will contribute to developing predictive models for reactor behavior, facilitating early detection of anomalies such as temperature deviations, pressure surges, or chemical imbalances. This research contributes to the existing body of knowledge by advancing IoT-based sensor technologies specifically tailored for harsh industrial environments, integrating sensor data analytics with real-time monitoring frameworks, and demonstrating the feasibility of scalable, intelligent sensor networks for chemical process control. The findings will inform best practices for deploying IoT sensors in industrial chemical processes, with implications for improving process safety, operational efficiency, and environmental compliance. The study concludes that the implementation of IoT-enabled sensors can revolutionize chemical reactor monitoring, making it more proactive and data-driven. Recommendations arising from this research include the adoption of standardized sensor calibration procedures for industrial applications, the integration of machine learning algorithms for predictive analytics, and development of industrial protocols to facilitate large-scale deployment of IoT sensor networks. Future studies should explore the deployment of these sensor systems in full-scale industrial reactors, assess long-term durability, and investigate the integration with existing industrial control systems to realize comprehensive smart manufacturing ecosystems. Overall, this research underscores the transformative potential of IoT technology in chemical process monitoring, aiming to foster safer, more efficient, and sustainable chemical manufacturing practices.