Hi, I'm Akash
Embedded Systems & Robotics Developer passionate about building intelligent hardware solutions using IoT and automation.
Embedded Systems & Robotics Developer passionate about building intelligent hardware solutions using IoT and automation.
I’m Akash Shelar, an Electronics and Computer Engineering professional, passionate about Embedded Systems, Robotics, and IoT. I build real-world hardware solutions using microcontrollers, sensors, and intelligent automation, and I continuously refine my skills to design reliable and practical embedded systems.
Embedded C / C++, Firmware, Hardware Debugging
Arduino, ESP8266, Sensors & Actuators
Robot Design, Motor Control, Automation
IoT Systems, Cloud, TCP/IP, NAT
Arduino IDE, Wireshark, Nmap
Leadership, Teamwork, Problem Solving
I enjoy designing embedded systems from the ground up — choosing the right microcontroller, planning hardware connections, and writing firmware that works reliably in real-world conditions. I focus on building systems that are simple, efficient, and practical.
I work on connecting software with hardware by interfacing sensors, motors, displays, and communication modules. Bringing hardware and code together to form a complete working system is one of the parts I enjoy the most.
I build robotics and automation systems that involve motion control, decision-making logic, and system coordination. I like working on problems where mechanical movement and embedded logic come together to perform tasks intelligently.
I develop IoT-based systems that can collect data, communicate over the internet, and allow remote monitoring or control. I focus on making connected devices reliable, responsive, and easy to manage.
I spend a lot of time debugging hardware and firmware issues, whether it’s signal problems, timing issues, or logic errors. I believe debugging is a core skill and enjoy improving system performance through testing and optimization.
I joined Team Sphinx in 2023 when the team was preparing for DD Robocon.
I worked on electronics, coding, and sensor–actuator interfacing.
I supported robot design, fabrication, and worked under time pressure.
In 2024, I became Vice Captain and managed a team of around 16 members.
This journey shaped my leadership and system-level problem-solving skills.
I participated in the Robo War of Robots competition with my team.
I worked on robot electronics, motor control, and quick debugging.
The matches required fast decisions and reliable hardware.
I learned how response time affects competitive robots.
Our team secured 2nd position at Amrutvahini College of Engineering.
I completed a Cyber Security internship focused on real-world threats.
I worked on network security and vulnerability assessment.
I used tools like Wireshark and Burp Suite.
This internship improved my analytical mindset.
It helped me understand risks in IoT and connected systems.
After Robocon, I co-founded Ashapuri Automation & Services.
We worked on automation projects in agriculture and irrigation.
I was involved in system design and hardware integration.
This role exposed me to real client requirements.
It helped me understand real-world deployment challenges.
I am currently pursuing an Embedded Systems course at Emertxe Institute.
The course focuses on embedded C and system fundamentals.
I am strengthening low-level system understanding.
The training emphasizes practical and structured learning.
This supports my long-term career in embedded systems.
Registered industrial design for a Robotic Arm Gripper under the Indian Patent Office. This patent protects the mechanical design structure developed as part of an innovation-focused engineering project.
KODACY (In Association with SPACE)
National Robotics Competition (Participant)
National Robotics Competition Secured 13th Rank (All India Level)
National Level Technical Event
This project focuses on building an intelligent border fencing system using embedded systems, sensors, and AI-based computer vision. The main aim of this project was to automatically detect intrusions near the border and reduce dependency on manual monitoring.
This system can be used in areas where strong and advanced safety is required, such as borders, restricted zones, and high-security regions. In this project, we designed a system that detects humans, animals, and abnormal activities and responds accordingly.
This was my final-year group project, where I worked as the group leader along with my team members and coordinated the overall system development.
In this project, I was responsible for deciding the complete project flow, methodology, and system design. Along with my team members, I planned the architecture, selected the components, worked on hardware integration, and contributed to PCB design and final report preparation.
For computer vision, I used the COCO dataset and implemented TensorFlow-based object detection to identify humans and animals near the border. Animal detection triggers an alert and a short buzzer activation to move the animal away without causing harm.
When a human intrusion is detected, the system sends an alert along with the captured image to the control room for monitoring and further action. An ultrasonic sensor helps measure the distance between the fence and the detected object.
To detect abnormal aerial activities such as drones or jets, an ultrasonic sensor is mounted on a servo motor to continuously scan the surroundings. For underground intrusions, a vibration sensor is used to detect digging attempts near the fence.
A sound sensor is integrated to detect abnormal sounds such as gunfire or explosions. Whenever suspicious activity is detected, the system immediately triggers alerts for security personnel.
A Raspberry Pi acts as the main processing unit to handle AI processing and decision- making, while an Arduino is used as the hardware controller for sensors and actuators.
Overall, this project helped me gain strong hands-on experience in embedded systems, AI-based computer vision, sensor integration, and real-world security system design while leading a team and delivering a complete working solution.
This project is a smart agriculture solution that monitors soil moisture, temperature, humidity, and light conditions in real time. Based on soil moisture levels, the system automatically controls a water pump using a relay to prevent over-watering or under-watering.
Sensor data is displayed live on a mobile dashboard, allowing remote monitoring and basic automation. This project helped me understand sensor interfacing, relay control, and IoT-based data visualization for agriculture applications.
I learned how CNC machines work by practically building and understanding a complete CNC system. The main aim of this project was to gain hands-on experience with motion control, firmware configuration, and machine calibration.
This project helped me understand how automated machines achieve precise movement along X, Y, and Z axes using stepper motors and firmware-controlled motion planning.
In this project, I used Marlin firmware with the MKS Robin Nano V3 board to control the CNC system. NEMA 17 stepper motors with A4988 motor drivers were used for accurate motion control.
I performed step size calibration and XYZ-axis calibration to achieve proper alignment and precision. I also learned how firmware parameters affect real-time machine behavior by editing and testing Marlin configurations.
The system was powered using a 24V SMPS and controlled through the MKS 43H display. This CNC setup can be used for applications such as PCB layout drawing, laser cutting, and writing CNC machines.
Overall, this project gave me strong hands-on experience in CNC systems, motion control, and firmware-based machine operation.
This project is an offline voice-controlled information system that listens to user commands and responds with both audio and on-screen text. When a keyword is spoken, the system plays the corresponding stored audio and displays the same information on a screen.
All content is stored locally using an SD card, so the system works without internet. It is ideal for museums, exhibitions, and educational kiosks where hands-free interaction is required.
I learned how embedded systems and IoT can be applied in smart retail by building this Smart Grocery Trolley. The main aim of this project was to reduce customer effort and waiting time at supermarket billing counters.
The trolley automatically follows the customer, scans products, and updates the bill in real time. It also supports digital payment and automatic bill printing, making shopping faster and more convenient.
This system can be used in supermarkets, malls, and smart retail stores. This project was designed and implemented individually by me.
I integrated embedded hardware, IoT communication, and AI-based vision to automate trolley movement, product scanning, and billing. Raspberry Pi 5 handled vision and billing logic, while Arduino controlled motors and sensors.
Human following was achieved using OpenCV and YOLO-based person detection. A barcode scanner fetched product details from a database and updated the bill instantly on the display screen.
After shopping, the customer can complete digital payment and receive an automatically printed bill. The system also detects unpaid exits and triggers an alarm, similar to existing retail security systems.
Overall, this project gave me hands-on experience in embedded systems, IoT integration, computer vision, and smart retail automation.
I developed this Lab Automation project to simplify how laboratory equipment is controlled and managed. The system is designed to provide both automated and manual control for flexibility.
I designed a custom control board capable of handling one fan with speed control and multiple 4-pin sockets for connecting lab equipment.
The system can be controlled using voice commands as well as through the Blynk IoT mobile application. To avoid complete dependency on IoT, manual push buttons were added directly on the board.
An IR remote control was also integrated to allow wireless operation. This project helped me understand how to combine hardware design, embedded control, and IoT into a practical laboratory automation solution.
I built this project to automate the daily playback of Hanuman Chalisa in temples without depending on manual operation. The system automatically switches ON the amplifier, plays the Chalisa once, and turns everything OFF at the correct time.
In this project, I used an ESP32 as the main controller along with an RTC module so that the system works accurately even without Wi-Fi connectivity.
Audio playback is handled using a DFPlayer module with MP3 files stored on an SD card. Manual control through a push button and remote control via a mobile app were also added for flexibility.
To ensure electrical safety, fuse protection and surge protection were included for the AC amplifier. This system is useful in temples where devotional activities must happen on time without human effort.
Overall, this project helped me apply embedded system concepts in a practical, real- world devotional automation setup.
This project is a smart door lock system that uses face recognition instead of keys or passwords. When a person stands in front of the camera, the system verifies the face and unlocks the door only for authorized users.
The entire process runs offline, making it secure and reliable. This project gave me hands-on experience with computer vision, Python, and hardware control using relays.
This project is my personal portfolio website, designed and developed completely from scratch to represent my work, skills, and journey as an electronics and embedded systems engineer. Instead of using ready-made templates, I focused on building a clean, modern, and interactive website that feels professional and easy to explore.
The website brings all my work together in one place — projects, experience, certificates, patents, and achievements — and presents them using smooth animations and an organized layout. Users can interact with different sections through animated tabs, click on images to view them in full screen, and navigate smoothly across the site without sudden jumps.
While building this website, I paid special attention to details like dark-theme aesthetics, spacing, readability, and responsiveness across different screen sizes. Features such as click-to-open image modals with close and ESC support, section-based navigation, and custom UI animations were carefully implemented to improve the overall user experience.This project helped me understand how real websites are structured, how UI and logic work together, and how small design decisions affect usability. It also improved my problem-solving skills, as I fixed layout issues, animation bugs, and interaction flows step by step during development.
I also purchased my own domain, akashshelar.in, and deployed the website online, making it easily accessible and professional to share with recruiters and collaborators.
Overall, this website is not just a portfolio — it reflects my learning process, creativity, and ability to design and build a complete system from the ground up.
Experience & Projects Highlights
Have a project idea, opportunity, or just want to connect? Feel free to reach out — I’d love to hear from you.