Estimating Pesticide Concentration with Smartphone

This is a multi-disciplinary research with an aim to empower everyone to be able to measure pesticide concentration present in the vegetables and fruits they buy by simply using their smartphones and a filter paper. The project is in collaboration with Dr. Basant Giri of Kathmandu Institute of Applied Sciences (KIAS).

Problem:

Paper-based analytical devices (PADs) offer a low-cost and accessible method for clinical diagnostics and environmental monitoring. However, they often lack sensitivity and selectivity compared to traditional spectrophotometer-based assays due to limitations in colorimetric detection. While visual inspection provides qualitative results, quantitative analysis requires image processing, which may not capture subtle color variations accurately. This limitation hampers the sensitivity and selectivity of PADs, particularly in detecting narrow wavelength signals.

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Research Aim:

The research aims to enhance the sensitivity and selectivity of paper-based analytical devices by developing computer vision algorithms in tandem with device development. By integrating computer vision and machine learning techniques, the goal is to provide a more accurate and precise measurement of analytes from images captured using standard smartphone cameras. Collaborative efforts between NAAMII and KIAS focus on exploring innovative approaches to address the challenges associated with colorimetric detection limitations in PADs.

Outcome So Far:

Initial investigations have commenced into the development of computer vision algorithms to enhance the sensitivity and selectivity of paper-based analytical devices $1$. Collaborative efforts between NAAMII and KIAS have laid the groundwork for exploring innovative solutions to address the challenges posed by colorimetric detection limitations. Ongoing research aims to further refine and optimize these algorithms in conjunction with device development, with the ultimate goal of providing a more accurate and reliable measurement platform for clinical diagnostics and environmental monitoring applications.

Refrence: 

Sharma, Niraj, Toni Barstis, and Basant Giri. “Advances in paper-analytical methods for pharmaceutical analysis.” European Journal of Pharmaceutical Sciences 111 (2018): 46-56. full-text-PDF

Team: Bishesh Khanal, Bidur Khanal, Basant Giri and the team from KIAS.