Electrical Engineering @ National Institute of Technology Calicut
Scroll for MoreAs an electrical engineering student with a strong focus on the Internet of Things and embedded technology, I'm actively looking for opportunities to use the technology I know to solve meaningful problems and enhance my learning.
I started Farm21 (farm21.in) with the aim to redefine agriculture in India, combining IoT and prediction models to create practical, scalable solutions to improve resource efficiency, and increase crop yields. Currently I'm working on the embedded system for the Farm21 platform, for which I developed a prototype ESP32 shield from scratch.
I spent the summer at Aqua Middle East, working with their R&D team as a project intern on creating an IoT-based pool and water management system. I contributed to both the embedded design and a market feasibility study that helped align technical innovation with business potential.
My work now focuses on edge intelligence, integrating TinyML with AWS IoT Core for on-device analytics. I'm developing a prototype that monitors 10+ water quality parameters in real time using embedded systems.
I'm eager to collaborate on projects that merge engineering and impact, and I'm actively exploring roles in embedded systems, IoT design, and product development.
Built a Firebase Realtime Database backend and integrated it with the Twilio API to send live soil-moisture data from ESP32 nodes, enabling users to monitor irrigation status and receive alerts in real time.
Designed and fabricated a custom ESP32-based PCB shield that integrates environmental sensors, relay control, power-management circuitry, and an OLED display for in-field diagnostics.
Deployed and maintained a live test node in Kasargode, Kerala for six months to evaluate climate-specific agricultural conditions, collecting data using Realtime DB and a Flash-based API that informed both hardware revisions and firmware optimizations.
Presented early product demos at Ekasva, a university startup expo, generating interest from alumni and collecting initial user feedback on UX and feature priorities.
Conducted feasibility research for indoor, container-based agriculture in the UAE, adapting Farm21's core sensing and control stack to arid-region constraints (high temperature, water scarcity, and controlled environments).
Supported the development of an upcoming IoT-based pool and water management system, enabling real-time monitoring, safety and control for smarter water use and maintenance.
Assisted with the initial PCB fabrication process for the first prototype, learning the execution hands-on from the team.
Integrated AI-driven n8n automations into team workflow and lead generation, improving efficiency and supporting better operational decisions.
Built an Agentic AI dashboard for KSUM's Build for India Hackathon using Amazon Bedrock and Nova Pro. Integrated simulated KSEB/KWA portal workflows via AgentCore Browser, and deployed a multimodal civic-monitoring chatbot with AWS Lambda + DynamoDB to drive proactive WhatsApp alerts.
LSTM-driven rain prediction using Python and TensorFlow, integrating Farm21's test node to collect real-time data, generating data-driven rain probability forecasts from field humidity and temperature compared with historic annual trends.
A custom ESP32 expansion shield built for Farm21. The board integrates environmental sensors, relays, power management, and an OLED display, designed for reliable end-to-end IoT deployment in real-world farm conditions.
Autonomous rover using Arduino Uno Q that navigates via IMU, captures images, and detects plant diseases using Edge Impulse's MobileNetV2 model. Targets potato plant disease detection with expandable model support for other crops via retraining.
Python program using Google Gemini API designed to create an LLM-based interaction with a reddit post, to streamline the process of summarizing and extracting valuable insights from Reddit posts.
A comprehensive web-based smart farm management platform built as the final project for CS50. The application provides farmers with real-time farm monitoring, data analysis, and decision support tools to optimize crop yields and resource management through an intuitive interface.