MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202641008154 A) filed by Dr. Naveen P; Dr. Deepali V Patil; Dr. Sonali V Patil; Shradha V Shilwant; M. Sandhiya; Hiral Patel; Joslyn Gracias; and Dr. N. Gopinath, Chennai, Tamil Nadu, on Jan. 28, for 'system and method for monitoring and predicting plastic waste decomposition using multi sensor data and machine learning.'
Inventor(s) include Dr. Naveen P; Dr. Deepali V Patil; Dr. Sonali V Patil; Shradha V Shilwant; M. Sandhiya; Hiral Patel; Joslyn Gracias; and Dr. N. Gopinath.
The application for the patent was published on March 13, under issue no. 11/2026.
According to the abstract released by the Intellectual Property India: "The current innovation pertains to a smart system and technique that use environmental sensors, image systems, and machine learning algorithms to track and forecast the breakdown of plastic trash. Whether in a lab or out in nature, the technology can automatically evaluate the rate of plastic breakdown in real time. Biological, chemical, and hybrid degradation mechanisms are all supported by the system's breakdown chamber, which may hold samples of plastic garbage. In order to keep tabs on the factors that affect plastic breakdown, the chamber is fitted with a number of environmental sensors. These include humidity, gas, pH, and temperature sensors. In order to identify surface-level and physical changes happening during degradation, a visual imaging device takes high-resolution pictures of the plastics. A microcontroller or processing unit is in charge of acquiring, syncing, and preprocessing data in real-time and is connected to all image and sensing components. Using trends and historical information, machine learning models are trained to. categorize plastic kinds, identify stages of breakdown, and forecast degradation rates. These models are then applied to the gathered environmental and visual data. Evaluating the effectiveness of decomposition and optimizing experimental settings are both made possible by these predictive capacities. A dashboard interface is also a part of the system, which allows users to easily see patterns in sensor data, images, and predictions. You may use the dashboard to keep tabs on things in real time, see how far along you are, and make decisions based on facts. Deployment in research, field, industrial, and laboratory settings is possible thanks to the invention's modular and scalable architecture. The technology helps with sustainable waste management by offering an intelligent, automated, and non-destructive method to evaluate plastic degradation. It also makes it easier to analyze, monitor, and optimize the processesjnvolved in plastic decomposition."
Disclaimer: Curated by HT Syndication.
