Client consultation and system design: Worked with the client to develop a state of the art fireplace control system using hybrid mist and bio-ethanol technologies. This involved extensive consultation to understand and integrate the desired functionality into a cohesive system architecture using ESP32 microcontrollers.

Hardware configuration and integration:

• Designed and configured a user-facing display board to provide real-time information and control options directly to the user
• Implemented a Bluetooth Low Energy (BLE) HID remote control to allow users to adjust flame levels remotely, improving the user interface and accessibility of the fireplace system

Networked control system implementation:

• Developed a master-slave configuration, connecting the display master card and a slave card via Ethernet CAT cable. This setup allows the master board to send operational commands to the slave board, ensuring coordinated control of the fireplace mechanisms
• Enables the slave board to operate independently via a BLE-connected application when not connected to the master display, allowing remote adjustment of flame levels and other operating parameters via the application

Web server and OTA functionality:

• A web server has been implemented on the ESP32 platform to facilitate remote monitoring and calibration of the fireplace system, providing a convenient interface for system maintenance and adjustments
• Integrated Over-The-Air (OTA) functionality to enable seamless firmware updates, ensuring the system is kept up to date with the latest features and security patches without requiring physical access to the hardware

Accelerometer enhancement: Successfully enhanced the firmware for the IIS3DWB accelerometer via SPI to achieve a high output data rate (ODR) of 26.66kHz. This upgrade significantly improved accuracy in motion tracking applications, demonstrating deep engineering expertise in optimising sensor performance

Magnetometer integration and upgrade planning:

The IIS2MDC magnetometer was integrated via I2C, laying the groundwork for future pin reassignment to improve data integrity and sensor performance. This planned enhancement aims to minimise data corruption and maximise the reliability of magnetic field measurements

Software maintenance and new features:

Regular software maintenance, including debugging, optimising existing code and updating firmware to support new hardware configurations. This ensures that the system remains robust and scalable
New features are developed and integrated into the firmware in response to evolving project requirements and customer feedback to improve system functionality and user experience

Project overview and customer collaboration: Working with a client to design and program an automated cocktail machine capable of dispensing a variety of alcoholic and non-alcoholic beverages. This project involved extensive consultation to understand the customer's needs and operational requirements.

System design and configuration:

• Designed a system consisting of 28 individual containers, each dedicated to a different beverage, to maximise the variety of cocktails that could be mixed.
• Implemented 28 dedicated pumps to dispense the drinks, ensuring precise control over the quantity and mix of drinks.
• Integrated 28 relays to manage the operation of the solenoid valves that control the flow from each container, increasing the efficiency and reliability of the dispensing process.

Hardware integration and programming:

• Used an ESP32 microcontroller as the central processing unit, demonstrating expertise in using advanced microcontrollers for complex automation tasks.
• Connected a tablet interface for user interaction, allowing customers or operators to select drinks via a user-friendly graphical interface.
• Used a USB-TTL converter with cable to facilitate communication between the tablet and the ESP32, ensuring smooth and responsive user interaction.

Software development and interface design:

• Developed firmware for the ESP32, programming the device to co-ordinate the operation of pumps and relays based on user input to achieve automated, accurate cocktail mixing.
• Created an intuitive interface on the tablet for easy cocktail selection, enhancing the user experience by simplifying the operation of the machine.

System design and integration:

- Developed a door scanner capable of reading barcodes and QR codes using a QR600 series scanner, integrating state-of-the-art scanning technology for fast and reliable access control. Utilised an ESP32 microcontroller to manage data acquisition from the QR scanner

Communication and protocol implementation:

• Implemented a specific protocol structure according to the documentation provided by the customer, ensuring that data transmission met security and efficiency standards
• Maintained continuous communication with the customer throughout the development process to confirm that the project was in line with their expectations and adapted the system based on their feedback

Manufacturer collaboration:

• Liaised with the QR scanner manufacturer for technical support, leveraging their expertise to optimise the integration and performance of the scanning hardware
• Coordinated troubleshooting and fine-tuning of scanner settings to improve system reliability and user experience

Client collaboration: Working with the customer to understand their specific issues and requirements to ensure targeted troubleshooting of the plant monitoring system.
Hardware troubleshooting: Assisted in identifying and resolving hardware issues within the system, with particular focus on the ESP32 and DHT sensor connections, which improved the operational reliability of the system

Software development: Programmed the ESP32 to efficiently retrieve environmental data from the DHT sensors, incorporating error handling to improve data reliability

Display implementation: Configured a 7-segment display for real-time temperature and humidity readings, providing a user-friendly interface for immediate environmental feedback

Client Collaboration: Collaborated with the customer throughout the project to accurately determine requirements and refine system specifications, ensuring that the final setup met all operational requirements for real-time water quality monitoring in an industrial environment

Hardware Integration: Configured and installed multiple sensors on an Olimex ESP32-POE-ISO, including a DFrobot analogue dissolved oxygen sensor, a DS18B20 temperature sensor and a pH sensor, ensuring reliable measurement of critical water quality parameters

Software development: Programmed the ESP32 using the Arduino core to handle sensor data acquisition, processing and error checking. Implemented AsyncWebServer to provide real-time sensor data via simple HTTP endpoints

Network configuration: Set up both Ethernet and WiFi connectivity options on the ESP32, allowing seamless integration into existing industrial network infrastructures and ensuring reliable data communication

System calibration and validation: Perform comprehensive calibration of sensors to manufacturer specifications to ensure accuracy of pH, temperature, dissolved oxygen and oxygen saturation measurements

Web server implementation: Developed a user-friendly web server interface using ESPAsyncWebServer, providing endpoints for real-time data display including temperature (°C), dissolved oxygen (mg/L), oxygen saturation (%) and pH

Project scope and client interaction: Worked with the client to develop a voice-controlled smart lighting solution using Amazon Alexa and ESP32, with a focus on seamless integration and ease-of-use

Alexa skill design and deployment:

• Designed custom Alexa skills tailored to control lighting systems, allowing users to turn lights on and off using voice commands
• Deployed the Alexa skills on Amazon Web Services (AWS), leveraging the robust cloud infrastructure to ensure reliable and scalable voice command processing

IoT device configuration and registration:

• Configured and registered the ESP32-based smart light devices with AWS IoT Core, ensuring secure and efficient communication between the devices and cloud services

Serverless architecture implementation:

• Implemented AWS Lambda serverless functions to handle queries from Alexa. These functions processed voice commands and communicated with the IoT devices to control the lighting system

System integration and voice command optimisation:

• Integrated the smart lighting system with the Alexa ecosystem, testing and refining voice command recognition to ensure accuracy and ease of use