The project aims to develop a novel biosensor for detecting urea in agricultural runoff water, enhancing nitrogen use efficiency (NUE) and reducing environmental impact. It includes integrating the sensor into farm irrigation systems, conducting feas
Aflatoxin contamination in foodstuffs like groundnuts poses a significant health risk. Current detection methods are costly and time-consuming. The proposed biosensor technology aims to provide a rapid, affordable solution for detecting AFB1 contamin
The project aims to design specific DNA probes for detecting Shigella sp. and Salmonella in potable water, developing a sensitive biosensor by coupling novel receptors. It includes sensor fabrication, characterization, calibration, and cross-validati
The project aims to develop a theoretical framework to assess cognitive performance and create a product for early detection and rehabilitation of cognitive impairment. Objectives include evaluating factors affecting memory loss, developing a cogniti
The project aims to develop a scalable backend framework for IoT-based applications in the cloud. It focuses on optimizing data transfer, storage, and resource utilization by creating a microservices-based architecture. The framework will include API
The project focuses on addressing security and data integrity challenges in Wireless Body Area Networks (WBANs) used for monitoring physiological data. It aims to develop low-power cryptographic techniques for securing devices and tackle data anomaly
The project aims to develop a standalone Lab-On-Chip (LoC) microfluidics-based system for cell and tissue culture studies. It integrates subsystems for culture environment regulation, microfluidic cell culture devices, and detection capabilities. The
The project aims to develop a miniaturized, high-performance Microfluidic Enzymatic Bio-Fuel Cell (M-EBFC) as a reliable, continuous power source for wearable and implantable medical devices. It integrates bio-supercapacitors for interruption-free op
The project aims to develop a miniaturized electrochemical device for quantifying renal biomarkers (urea, uric acid, creatinine) using carbon-based electrodes. It includes electrochemical characterization, machine learning for data processing, IoT in
The project aims to isolate exosomes from individuals infected with Plasmodium spp., including those with severe disease (e.g., hepatic dysfunction, renal failure), and compare their protein or nucleic acid cargo with that of uninfected controls. The
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