Freelancer-logo
Log Ind Tilmeld
Opret et projekt

UDFORSK

C Programming Electrical Engineering Electronics Engineering Microcontroller
Profil coverbillede
Brug Avatar.

Sardar Hasnain A.

@Mahihassi

verified-v2.svgpreferred-freelancer-v3.svg
5,0
347

8,3

8,3

100%

Electrical Engineer | Embedded Systems

$20 USD / Time

・

Flag for

Pakistan (7:24 AM)

・

Tilmeldt april 11, 2020

・

33 Anbefalinger

$20 USD / Time

・

I am a dedicated Electrical Engineer with a Master’s in Embedded Systems, specializing in firmware development, PCB design, and complete IoT product engineering. From concept to market-ready product, I deliver robust embedded solutions that combine hardware, software, and intelligent connectivity. Core Expertise -> Microcontrollers & Embedded Systems: STM32, ESP32, TI Tiva, C2000, MSP430 (Texas Instruments), NXP LPC & [login to view URL] RT, Nordic nRF52/nRF53, Microchip PIC32 & dsPIC, Raspberry Pi, and Arduino. -> Firmware Development: Embedded C/C++, RTOS, DMA, peripheral drivers, wireless stacks (BLE, Wi-Fi, LoRa, Zigbee). -> PCB Design & RF Hardware: Professional PCB layouts using Altium Designer, KiCad, Eagle, EasyEDA and Target. Specialized in RF, IoT, and high-speed boards. -> FPGA Development: Verilog/VHDL for signal processing, hardware acceleration, and high-performance digital systems. -> AI, Machine Learning & Deep Learning: Intelligent algorithms for edge devices, control, and data analysis. -> Robotics & Control: Robotic platforms, precision motor control (FOC, PID), and industrial automation. -> Biomedical Instrumentation: Embedded systems for healthcare and diagnostic devices. -> CAD & Mechanical: 3D CAD modeling for custom housings and production-ready enclosures. Full Product Development Workflow From Idea → Prototype → Final Product System Architecture & Schematics Firmware Development (optimized embedded coding & drivers) PCB Design (multi-layer, RF, low-power, IoT-ready) AI/ML Integration (edge computing & analytics) IoT Connectivity (MQTT, APIs, BLE, Wi-Fi, LoRa, Zigbee) Web & Mobile App Development (real-time dashboards & control apps) Mechanical CAD (3D modeling & enclosures) Software Development Web Applications: Cloud dashboards, real-time monitoring, secure APIs, SaaS platforms. Mobile Applications: Cross-platform IoT control, monitoring, and productivity apps. IoT Communication: Secure & scalable device-to-cloud pipelines (MQTT, REST, WebSockets). Trading & FinTech: Algorithmic trading systems, exchange integrations (Binance, TradingView APIs). Game Development: WebGL, HTML5, Unity3D, 3ds Max, Maya, Unreal Engine 4/5, Godot. Emerging Tech: Blockchain & Web3 apps, AI-powered platforms, cloud-native solutions (AWS, Azure, GCP).

Verifikationer

Til tiden

93 %

Indenfor budgettet

92 %

Accept andel

80 %

Genansættelse andel

24 %

Freelancer Electrical Engineers Pakistan
Se alle Electrical Engineers i Pakistan

Portfolio-mappe

Portfolio-mappe

13642813
Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

Dual Piezoelectric Driver PCB

Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

13582314
NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

13642870
Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

AWS IoT-Enabled Methane Sensor

12575671
This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

12575745
This project involved developing a Bluetooth-enabled Android application designed to send text commands to multiple paired devices and play an MP3 file through the phone's 3.5mm audio jack. The application connects to STM32 microcontroller-based hardware equipped with a JDY-18 BT/BLE 4.2 wireless module, ensuring seamless data transmission. The app allows users to select an audio file, enter a command string, and pair with multiple IC modules. Once paired, the app sequentially connects to each device and sends the command while playing the audio. The software was developed in Android Studio, featuring a user-friendly GUI, Bluetooth device management, and real-time status updates via Toast messages. The project required extensive Bluetooth connectivity handling, asynchronous communication, and real-time device pairing. Challenges included optimizing connection stability, ensuring seamless device communication, and handling variable response times between devices.

Bluetooth-Based MP3 IOT App

7093638
Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

13642813
Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

Dual Piezoelectric Driver PCB

Designed and developed a dual-channel piezoelectric driver PCB for driving 1 MHz piezo transducers using the DRV2700 boost converter and ESP32-WROOM. The system features three voltage variants — 100 V, 22.36 V, and 15.6 V — and integrates battery charging, feedback monitoring, and Bluetooth control. Key highlights: Li-ion battery charging & protection via TP4056 + DW01A DRV2700 boost stage for high-voltage piezo drive INA290A1 current feedback amplifier for precise sensing ESP32-based control with PWM generation, Bluetooth, and status LEDs Complete Altium project with schematics, layout, 3D model, and Gerbers This board enables portable high-frequency piezo operation for industrial, medical, and sensing applications.

Dual Piezoelectric Driver PCB

13582314
NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

NFC-Based Access Control Bollard Designed and delivered a full IoT solution for secure access control. The product integrates: RFID (MFRC522) authentication with STM32 firmware Custom PCB + 3D CAD enclosure (fabricated & assembled) Cloud connectivity for remote monitoring and control AI-based data processing for usage insights and anomaly detection Web dashboard for device management and user access logs This end-to-end system was developed from schematic design to functional prototype, combining firmware, hardware, and software into a single complete product.

NFC-Based Access Control Bollard

13642870
Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

Developed a complete IoT pipeline for real-time methane and environmental data monitoring using ESP32 and AWS Cloud. The ESP32 collected temperature, humidity, and pressure readings and published them to AWS IoT Core via MQTT. Data was automatically routed to AWS Lambda, processed with Python (binary decoding + struct unpacking), and stored in DynamoDB. The system also included CloudWatch integration for monitoring Lambda triggers and data logs, enabling full cloud traceability from edge to storage. This end-to-end design covered firmware development, MQTT configuration, and AWS cloud integration.

AWS IoT-Enabled Methane Sensor

AWS IoT-Enabled Methane Sensor

12575671
This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

This project involved designing and implementing a biomedical signal acquisition system for EMG-based robotic arm control, integrating hardware, software, and signal processing to achieve real-time motion control. A custom PCB was developed using Target 3001!, incorporating instrumentation amplifiers (LT1014DN), optocouplers (K847PH), and high-pass filtering to ensure accurate muscle signal acquisition while eliminating noise. The DAQ6008 data acquisition module converted analog muscle signals into digital inputs for robotic actuation. The software architecture, developed in LabVIEW, implemented signal filtering, motor selection logic, and a graphical user interface (GUI) for real-time feedback and visualization. A band-pass filter (80Hz–500Hz) was applied to remove noise while preserving relevant EMG data, enabling precise motor control. The system utilized peak detection and threshold-based activation, ensuring muscle contractions triggered robotic movements. Challenges included PCB

EMG-Based Robotic Arm Control

12575745
This project involved developing a Bluetooth-enabled Android application designed to send text commands to multiple paired devices and play an MP3 file through the phone's 3.5mm audio jack. The application connects to STM32 microcontroller-based hardware equipped with a JDY-18 BT/BLE 4.2 wireless module, ensuring seamless data transmission. The app allows users to select an audio file, enter a command string, and pair with multiple IC modules. Once paired, the app sequentially connects to each device and sends the command while playing the audio. The software was developed in Android Studio, featuring a user-friendly GUI, Bluetooth device management, and real-time status updates via Toast messages. The project required extensive Bluetooth connectivity handling, asynchronous communication, and real-time device pairing. Challenges included optimizing connection stability, ensuring seamless device communication, and handling variable response times between devices.

Bluetooth-Based MP3 IOT App

7093638
Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

Delivered multiple projects using the TI Tiva TM4C123 microcontroller, combining embedded firmware with IoT integration. Key highlights include: Keypad Password Lock System – secure access control with local input and cloud data logging. Snake and D Game on LCD – custom-developed game logic with button controls and debounce handling. LED Control & Automation – GPIO-based lighting control with real-time updates. Servo Motor Control – precise motor actuation integrated with IoT commands. IoT Cloud Connectivity – data acquisition and remote monitoring through cloud dashboards.

TM4C123 IoT & Embedded Projects

5.0 · 347 Bedømmelser
Bedømmelser
S

FPL Optimization Solver • £275 GBP

Superb work as ever!

Sam H.

@samharwood8

•

Flag for

Guildford, United Kingdom

•

1 måned siden

Del

A

Complete IoT: Hardware to App Debugging • $375 USD

Awesome developer - provided a lot of assistance. Job finished within budget and on time - will use again. Thanks for all the hard work.

Andre S.

@andres054

•

Flag for

GAMBRILLS, United States

•

1 måned siden

Del

O

iOS App Bug Fixing + Web Frontend & Backend Stabilization • $$

Great experience working with Sardar and his team. They quickly understood the existing iOS app, web frontend, and backend codebase and accurately identified the root causes of several critical issues. App crashes, API inconsistencies, and frontend bugs were fixed cleanly without disrupting the overall architecture. Communication was clear and professional throughout, with regular updates shared along the way. The updated code was well-organized and pushed to Git for easy testing.

Omar B.

@omar3E

•

Flag for

Abu Dhabi, United Arab Emirates

•

2 måneder siden

Del

Brug Avatar.

Arduino Code for Sensor + LED Control • $85 USD

Great work overall. The implementation was clear, efficient, and easy to follow, with well-structured and readable code. The task was completed quickly, and the solution worked exactly as intended. Would gladly hire again for microcontroller-related work.

Bo Ok L.

@bemorechill

•

Flag for

Los Angeles, United States

•

2 måneder siden

Del

Brug Avatar.

Raspberry Pi Bug Fixing & Debugging • $100 USD

Sardar did a great job on this project. He was professional, responsive, and very clear in his communication. He quickly understood the requirements, provided helpful insights, and delivered quality work on time. I would definitely recommend Sardar and look forward to working with him again.

Bo Ok L.

@bemorechill

•

Flag for

Los Angeles, United States

•

2 måneder siden

Del

Erfaring

Founder & Chief Executive Officer (CEO)

maj, 2020 - Til stede

•

5 år, 8 måneder

MHTechFusion

maj, 2020 - Til stede

•

5 år, 8 måneder

Founder & CEO of MHTechFusion, leading embedded systems, electronics, PCB design, firmware, and IoT projects for international clients. Also overseeing cloud infrastructure, AI/ML solutions, and full-stack app & web development initiatives. Responsible for technical leadership, system architecture, team coordination, and end-to-end project delivery with a strong focus on quality, scalability, and reliability.

Flag for

Freiburg im Breisgau, Germany

maj, 2020 - Til stede

•

5 år, 8 måneder

Uddannelse

Albert-Ludwigs-Universität Freiburg im Breisgau

2022 - 2024

•

2 år

Master's of Embedded Systems

Flag for

Germany

2022 - 2024

•

2 år

National University of Science and Technology

2017 - 2021

•

4 år

Electrical Engineering

Flag for

Pakistan

2017 - 2021

•

4 år

Kvalifikationer

AI At the Edge (FPGAS)

2022

AI Lounge

Artificial Intelligence Workshop: -> Convoluted Neural Networking -> Computer Vision -> Reinforcement Learning -> Speech Recognition -> Verilog/VHDL

2022

Certificeringer

Basic Numeracy - Level 1

Basic Numeracy

P

Preferred Freelancer Program SLA

Android - Level 1

Android Development

Freelancer-logo Denmark / Dansk
Hjælp & Support

Freelancer

KategorierProjekterKonkurrencerFreelancereVirksomhedInnovationsudfordringerAI udviklingMedlemskabForetrukken Freelancer-programProjektledelseLokale jobsPhoto AnywhereFremvisningAPI for udviklereBliv Verificeret

Om

Om osSådan fungerer detSikkerhedInvestorSitemapHistorierI nyhederneTeamTildelte priserPressemeddelelserKarrierer

Betingelser

PrivatlivspolitikVilkår og betingelserCopyright politikAdfærdskodeksGebyrer og afgifter

Partnere

Escrow.comLoadshiftWarrior Forum

Apps

Apple App Store logoGoogle Play-logo

Registrerede brugere

Oprettede jobs i alt

Freelancer ® is a registered Trademark of Freelancer Technology Pty Limited (ACN 142 189 759)

Copyright © 2026 Freelancer Technology Pty Limited (ACN 142 189 759)