MUMBAI, India, March 13 -- Intellectual Property India has published a patent application (202631026548 A) filed by Sanchita Paul; Abhinandan Chatterjee; and Rupa Verma, Ranchi, Jharkhand, on March 6, for 'next-gen iot ecosystem for vector -borne disease surveillance and early warning in community health.'

Inventor(s) include Sanchita Paul; Abhinandan Chatterjee; and Rupa Verma.

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 present invention discloses an intelligent portable vector surveillance and multi-disease outbreak prediction system designed for geographically distributed and vector-endemic regions requiring real-time monitoring and early warning of mosquito-borne diseases. The system comprises a custom-designed printed circuit board (PCB) integrated with an Arduino Nano RP2040 microcontroller and an NVIDIA Jetson Nano edge computing module, enabling coordinated data acquisition, processing, and transmission. The PCB interfaces with multiple environmental sensing modules and a mosquito imaging unit to collect synchronized multimodal data. Environmental sensors measure parameters including temperature, humidity, rainfall, soil moisture, and water stagnation, which influence mosquito breeding conditions. A smart mosquito trapping unit with an embedded camera captures periodic images or video of insects present in the monitored area. These images are processed using an AlexNet-based convolutional neural network (CNN) to perform mosquito segmentation, species classification, and vector density estimation for species such as Anopheles, Aedes, Culex, and Phlebotomus. Environmental and entomological data are preprocessed, time stamped, and transmitted wirelessly to a cloud platform using secure communication protocols. The integrated dataset is analyzed using machine learning algorithms including SVM, Random Forest, Gradient Boosting, XGBoost, and a Multi-Task Multi-Channel Nested LSTM model for outbreak prediction. The system generates hotspot alerts and visualizes risk patterns through a dashboard and mobile interface, enabling timely public health intervention."

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