Pinned Repositories
3TierArchitecture-Smarthome-Simulation-with-Database-using-Tkinter
Featuring an advanced interface. Integrated a SQLite database to manage user authority lists, enhancing security and access control. The project adheres to a predefined rubric, ensuring comprehensive coverage of requirements and robust functionality.
Face-Recognition-Attendance-System-with-Arduino-and-Realtime-Database
The system has a UI that displays real-time sensor readings and actuator status, student’s information, and camera feed. When the system recognised a face, the actuator is activated. All this information is then updated in real-time to Firebase.
Fake-Job-Posting-using-ML
Using Logistic Regression, Naive Bayes, Radial Basis Function SVM, Random Forest, Extra Trees Classifier, and Single-layer Neural Network to find the best predictive model. NLP is also used in the code to identify patterns that distinguish fake job postings from legitimate ones. Datasets are acquired from Kaggle. Code explanations is in the code.
Kanban-System-Simulation
Kanban order simulation using RFID and QR. All data from each station is sent in JSON format with MQTT to a server which later is processed to the database. It includes all station’s progress and material amounts, which then logged and shown on a UI. This project is made by 3 people.
MoltenCrust
Smart-Hospital-System-with-Django-NodeRED-Machine-Learning-MQTT
Simulates sensor readings from Node-RED via an MQTT out node. Implemented logistic regression to analyze sensor data from Node-RED, determining actuator status based on the predictions. The system and its subsystems each feature their own web UI, providing real-time monitoring capabilities. Created in an environment.
MoltenCrust's Repositories
MoltenCrust/3TierArchitecture-Smarthome-Simulation-with-Database-using-Tkinter
Featuring an advanced interface. Integrated a SQLite database to manage user authority lists, enhancing security and access control. The project adheres to a predefined rubric, ensuring comprehensive coverage of requirements and robust functionality.
MoltenCrust/Face-Recognition-Attendance-System-with-Arduino-and-Realtime-Database
The system has a UI that displays real-time sensor readings and actuator status, student’s information, and camera feed. When the system recognised a face, the actuator is activated. All this information is then updated in real-time to Firebase.
MoltenCrust/Fake-Job-Posting-using-ML
Using Logistic Regression, Naive Bayes, Radial Basis Function SVM, Random Forest, Extra Trees Classifier, and Single-layer Neural Network to find the best predictive model. NLP is also used in the code to identify patterns that distinguish fake job postings from legitimate ones. Datasets are acquired from Kaggle. Code explanations is in the code.
MoltenCrust/Kanban-System-Simulation
Kanban order simulation using RFID and QR. All data from each station is sent in JSON format with MQTT to a server which later is processed to the database. It includes all station’s progress and material amounts, which then logged and shown on a UI. This project is made by 3 people.
MoltenCrust/MoltenCrust
MoltenCrust/Smart-Hospital-System-with-Django-NodeRED-Machine-Learning-MQTT
Simulates sensor readings from Node-RED via an MQTT out node. Implemented logistic regression to analyze sensor data from Node-RED, determining actuator status based on the predictions. The system and its subsystems each feature their own web UI, providing real-time monitoring capabilities. Created in an environment.