// 01 — MSc Thesis
Real-Time IoT Resource Monitoring and Analytics Platform
Designed and implemented a real-time IoT system for operational efficiency in service environments.
The architecture spanned embedded edge nodes (ESP32-S3 with FreeRTOS), a local MQTT broker,
a real-time Node-RED analytics dashboard, and a multi-node Python simulation layer,
demonstrating end-to-end solution delivery from firmware to cloud-ready data pipelines.
ESP32-S3
FreeRTOS
MQTT
Node-RED
Raspberry Pi
Python
IoT
// 02 — Cloud & Edge Computing
Cloud-Native Web App with GenAI & Weather Services
Built a full-stack cloud application on Google Cloud Platform with serverless weather API
integration, a containerized GenAI service (image/text generation), and a CRUD backend
with NoSQL database and object storage. Deployed behind an API Gateway with Swagger UI
documentation and OpenAPI specs.
Google Cloud
Serverless
Containers
REST API
GenAI
NoSQL
// 03 — Embedded Systems
Snake Game with Color-Based Object Control
Built a dual-control Snake game using ESP32-S3 as the game server in WiFi AP mode,
with Python/Pygame for rendering, OpenCV for real-time red-object color tracking,
and a secondary ESP32 for physical button control. RGB LED and buzzer feedback on
hardware. Communication via WebSockets.
ESP32-S3
WebSocket
Python
OpenCV
Pygame
Computer Vision
// 04 — Graduate Coursework · Lab
Smart Home Automation via MQTT in Cisco Packet Tracer
Simulated a scalable smart home system with MQTT protocol in Cisco Packet Tracer.
Deployed MQTT broker/subscriber architecture controlling appliances (fans, lamps,
ACs) across multiple rooms via a smartphone interface, with wired + wireless network integration.
MQTT
Cisco Packet Tracer
IoT
Network Design
// 05 — Graduation Project (BSc)
Customized & Smart Vending Machine
Designed and built a self-cooking hardware vending machine with HMI interface,
state-machine-driven embedded firmware, web application integration, and an owner
dashboard for tracking ingredients, freshness, and maintenance alerts.
Embedded C
State Machine
HMI
Web App
Hardware
// 06 — Security & Networking
Cryptographically Secured Client–Server Communication
Built a Python socket-based client-server application with SHA-256 message integrity
verification. Implemented a lightweight request/response protocol with error handling
and validated correctness with structured test cases.
Python
SHA-256
Network Security
Socket Programming
// 07 — Networking
Home Network & IP Surveillance Deployment
End-to-end structured cabling deployment: terminated Ethernet cables, installed wall
outlets, labeled switch ports, configured router + mesh Wi-Fi coverage, and integrated
a camera surveillance system with a dedicated gateway.
Structured Cabling
VLAN
Mesh Wi-Fi
IP Surveillance
// 08 — Event Tech
NFC-Based Gamification System — KFUPM Gaming+
Designed and implemented an NFC-based event gamification platform with MQTT
asynchronous messaging. Contributed to protocol selection, edge device selection,
and network topology design under tight budget constraints for a 120+ participant event.
NFC
MQTT
Edge Devices
System Design
// 09 — Graduate Coursework · Lab
Secure IoT Communication — Cryptographic Protocols & MQTT Hardening
Implemented end-to-end cryptographic security between IoT devices using Diffie-Hellman key exchange,
XOR-based symmetric encryption, and HMAC message authentication in Cisco Packet Tracer.
Extended to MQTT with a TLS-style handshake, broker ACL authorization, and certificate-based
client identity verification, simulated with Python scripted logic for automated key negotiation and integrity checks.
Diffie-Hellman
HMAC
TLS
MQTT Security
Cisco Packet Tracer
Python
IoT Security
// 10 — Graduate Coursework · Guided Analysis
Industrial Fault Detection on the Tennessee Eastman Process
Analysed fault IDV(14), a sticking reactor cooling water valve, on the Tennessee Eastman Process
benchmark. Ran closed-loop and open-loop simulations (53 variables, 722 samples) to isolate a pure-variance
fault signature with >1,000% standard deviation increase and near-zero mean shift.
Implemented a statistical threshold detector achieving 99.4% detection rate with a 40-second delay,
and compared Random Forest (99.45% accuracy, ROC-AUC 0.9916) against Logistic Regression,
demonstrating that algorithm selection must be driven by fault physics.
Tennessee Eastman Process
Fault Detection
Python
Random Forest
scikit-learn
IIoT Analytics
Industrial Systems