Engineered a touch-based smart home switch utilizing advanced microcontrollers for versatile IoT control. Designed and implemented AC and DC power handling systems, along with analog, digital, and mixed-signal circuitry, to ensure optimized performance and reliability.Technical Implementation:Developed a smart home switch incorporating powerful microcontrollers to enable intuitive touch-based control. The design featured robust power handling systems for both AC and DC applications. Integrated analog, digital, and mixed-signal circuitry to enhance functionality, performance, and reliability of the switch.Key Features:- Touch-Based Control: Provides intuitive and user-friendly operation for smart home applications.- AC/DC Power Handling: Ensures reliable performance across different power types.- Advanced Circuitry: Combines analog, digital, and mixed-signal components for optimized functionality.Skills and Tools:- Microcontroller Design: For versatile IoT control.- Power Handling Systems: AC and DC power management.- Circuit Design: Analog, digital, and mixed-signal circuitry for performance optimization.Team Members:- Saurabh Patil - IoT,Tech LeadThe smart home switch delivers seamless touch-based control with reliable AC and DC power handling, supported by advanced circuitry for superior performance and efficiency in IoT applications.

Project Overview:Integrated a rebooter sensor into an Environmental Monitoring System to enhance the monitoring and management of server room conditions over IP. This integration improved the system's capability to track environmental and security parameters, providing early warning mechanisms to preempt critical events and prevent potential disasters.Technical Implementation:Incorporated a rebooter sensor into the existing environmental monitoring system, enabling real-time tracking and management of server room conditions. The system, now equipped with advanced IP-based monitoring, alerts operators to potential issues before they escalate, ensuring proactive measures and system reliability.Key Features:Enhanced Monitoring: Real-time IP-based tracking of environmental and security conditions.Early Warning Mechanisms: Alerts for potential critical events to prevent disasters.Improved System Reliability: Proactive management and early intervention capabilities.Skills and Tools:IP-Based Monitoring: For remote environmental and security tracking.Sensor Integration: Incorporating rebooter sensors for enhanced system capabilities.Early Warning Systems: For timely alerts and preventive actions.Team Members: Suvidh Kankariya Tech Lead,Solon,OH,USAThe enhanced Environmental Monitoring System now offers robust monitoring and early warning capabilities, significantly improving the ability to manage server room conditions and preventing potential critical events.

Project Overview:Designed and developed hardware for monitoring CNC machines, capturing key operational metrics such as active and idle times. Created an IoT dashboard to visualize performance data, providing real-time insights and analytics to drive efficiency improvements.Technical Implementation:Engineered hardware to interface with CNC machines, collecting data on machine activity and downtime. Integrated sensors and communication modules to transmit data to a centralized IoT dashboard. The dashboard visualizes performance metrics, enabling operators to monitor machine efficiency and make informed decisions.Key Features:- Operational Metrics Monitoring:Tracks active and idle times for CNC machines.- IoT Dashboard: Provides real-time data visualization and analytics.- Efficiency Insights: Enables improvements through detailed performance analysis.Skills and Tools:- Hardware Design: For integrating sensors and communication modules.- IoT Dashboard Development: For real-time data visualization.- Data Analytics: For performance insights and efficiency improvements.Team Members:- Mahesh Shahane , Chief Technology Officer at Heatcon Systems - Sensing & Control SolutionsOutcome:The monitoring system and IoT dashboard significantly enhanced CNC machine performance by providing real-time data and analytics, leading to improved operational efficiency and reduced downtime.

Launched an online platform offering practical and natural health solutions for busy professionals andentrepreneurs. The product integrates diet and streamlined workout routines to achieve fat loss or muscle gain through a proven 6-step habit installation system. As a co-founder, I secured investors, managed client-side activities, and led the technical development of the startup.

Project Overview:Developed an IoT system leveraging LoRa technology for low-power, long-range communication. This system integrates sensors via SPI communication to monitor soil parameters, designed specifically for agricultural scientists to enhance crop breeding and improve crop quality.Technical Implementation:Implemented a network of sensors connected through SPI communication, enabling precise soil monitoring. Utilized LoRa technology for long-range, low-power data transmission, ideal for remote agricultural environments. The system provides real-time data on soil health, facilitating informed decision-making for crop management.Key Features:- LoRa Communication: Ensures low-power, long-range connectivity for remote monitoring.- SPI Sensors: Accurately measures various soil parameters.- Real-Time Data: Provides timely insights for crop management.Skills and Tools:- LoRa Technology: For long-range, low-power communication.- SPI Communication: For sensor integration.- IoT Design: For system architecture development.Team Members:- Praveen Pankajakshan, Principal Data Science Manager India- Harshit Lohani , Data ScientistOutcome:This IoT system enhances agricultural practices by providing detailed, real-time soil data, supporting improved crop breeding and quality.

Project Overview:Priviledged to be the part of design and development of an IoT module for monitoring Automated Guided Vehicles (AGVs) in an industrial setting. This project aimed to enhance AGV efficiency by providing real-time data on uptime, battery charge, distance covered, temperature, and rest time. The system facilitated proactive maintenance, reducing downtime and boosting productivity.Technical Implementation:The IoT module integrated with sensors using UART, I2C, and SPI protocols for comprehensive data acquisition across AGV models. Using M-Duino and Intel Upboard platforms, it processed data efficiently and enabled real-time analysis. REST APIs facilitated seamless communication with central servers, integrating with industrial monitoring systems for immediate access to AGV data.Key Features:- Uptime Monitoring: Real-time tracking for anomaly detection.- Battery Monitoring: Continuous tracking with low charge alerts.- Distance & Temperature Tracking: Measures distance and temperature to ensure safe operation.- Rest Time Analysis: Records rest periods to optimize usage.Skills and Tools:- REST APIs: For data transmission.- M-Duino & Intel Upboard: For sensor integration and processing.- Serial Communications (UART, I2C, SPI): For reliable communication.- Python IDLE & Raspberry Pi 3B+: For data processing and tasks.- Rotary Encoder: For precise distance measurement.Team Members:- Bhavesh D Vagadiya - Tech Lead, Mobile Robotics- Abhijeet Gurav Embedded Development Engineer- Snehil Wani - Full Stack Developer at Rucha Group AurangabadOutcome:The IoT module enhanced AGV efficiency by providing real-time monitoring and actionable insights, showcasing the potential of Industrial IoT technologies in modern manufacturing.

Managed the Sale of Bolt IoT Products: Developed and executed social media strategies to boost product visibility and drive sales.Conducted Awareness Workshops: Organized and led workshops to educate participants on IoT technologies and applications.Studied ESP-Based Systems with Sensor Implementations: Investigated and analyzed ESP8266-based systems for integrating and optimizing sensor technologies.