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Sardar Hasnain A.

@Mahihassi

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5,0
354

8,4

8,4

100%

Electrical Engineer | Embedded Systems

$20 USD / hora

・

Bandeira do(a)

Pakistan (8:12 AM)

・

Entrou em abril 11, 2020

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33 Recomendações

$20 USD / hora

・

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).

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No prazo

94%

No orçamento

93%

Índice de aceitação

80%

Índice de recontratação

23%

Freelancer Electrical Engineers Pakistan
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Portfólio

Portfólio

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 · 354 Avaliações
Avaliações
S

Fantasy Sports Optimization System Development -- 2 • £520 GBP

Excellent developer with knowledge of all aspects of optimisation.

Sam H.

@samharwood8

•

Bandeira do(a)

Guildford, United Kingdom

•

há 3 dias

Compartilhar

F

New-Tech Electric Prototype Development -- 2 • $350 USD

Good work and great communication

Moulay F.

@farids87

•

Bandeira do(a)

Knislinge, Sweden

•

há 10 dias

Compartilhar

R

Modular Audio I/O Hardware System - PCB • $1.412,50 USD

These guys are amazing. They gave me nothing to complain about. They are very professional. They clearly know what they are doing. They communicated perfectly at every stage of the project and the quality of the designs they produced was outstanding. I (literally) could not be happier with my experience. They will be my first choice in any future projects. THANKS GUYS!

Rick M.

@rickmcneely

•

Bandeira do(a)

Oreana, United States

•

há 13 dias

Compartilhar

A

Live English-French and English-SpanishTranslator: PC & Embedded • $$$

Great partner to team with and collaborate.

Andre M.

@apmckinney0383

•

Bandeira do(a)

COLUMBIA, United States

•

há 25 dias

Compartilhar

R

Dedicated SWD Programmer Development • $4.151,50 USD

well implementation. our project work successfully

Raion R.

@raion23

•

Bandeira do(a)

Daejeon, Korea, Republic of

•

há 1 mês

Compartilhar

Experiência

Founder & Chief Executive Officer (CEO)

mai., 2020 - Presente

•

5 anos, 9 meses

MHTechFusion

mai., 2020 - Presente

•

5 anos, 9 meses

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.

Bandeira do(a)

Freiburg im Breisgau, Germany

mai., 2020 - Presente

•

5 anos, 9 meses

Educação

Albert-Ludwigs-Universität Freiburg im Breisgau

2022 - 2024

•

2 anos

Master's of Embedded Systems

Bandeira do(a)

Germany

2022 - 2024

•

2 anos

National University of Science and Technology

2017 - 2021

•

4 anos

Electrical Engineering

Bandeira do(a)

Pakistan

2017 - 2021

•

4 anos

Qualificações

AI At the Edge (FPGAS)

2022

AI Lounge

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

2022

Certificações

Basic Numeracy - Level 1

Basic Numeracy

P

Preferred Freelancer Program SLA

Android - Level 1

Android Development

Logotipo do Freelancer Portugal / Português
Ajuda & Suporte

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