International Journal of Scientific Research and Engineering Development

In recent years, monitoring microbial activity has played a key role in multiple disciplines including healthcare, agriculture, biotechnology, food safety, and environmental stewardship. Traditional methods of analyzing microorganisms have been based on laboratory testing which often requires long wait times for results, specialized equipment, and manual labor; therefore, detecting microbial irregularities and/or risks for contamination has proven to be increasingly difficult. In light of these issues, this study proposes a new intelligent biosensor-based system (MYCOCHIP) with a novel ability to use deep learning techniques to predict and analyze microbial behavior. The framework offers a hybrid approach by combining biosensor technology with advanced computational models to continually monitor both the environmental and microbial conditions. The data from the biosensors including temperature/humidity, pH/chemical concentration, and number of microorganisms found within the environment are processed and analyzed using Artificial Neural Networks (ANNs), Deep Neural Networks (DNNs), and Long Short-Term Memory (LSTM) models. The system not only predicts growth patterns but also assesses the risk of contamination before becoming critical. There is an Intelligent Causal Analysis module within the system which aids in determining the driving forces behind microbial activity and provides an avenue for users to gain meaningful insight. There is a centralized web-based dashboard that enables real-time monitoring and visualization of analytical results and the generation of reports. In addition, automated email and SMS notifications will be sent directly to users when abnormal microbial behavior has been detected.

M.Vasuki, R.Aravind,"MYCOCHIP: Intelligent Biosensor-Based Prediction and Analysis of Microbial Behavior Deep Learning" International Journal of Scientific Research and Engineering Development, V9(3): Page(2045-2050) May-June 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.