WANG SAI (0367388)

 CV&NLP Task 3 ToDo: For this group assignment, we plan to utilise facial recognition technology to identify the unique facial features of three members, thereby directing them to their respective rooms. Processing: My first step was to import the House models of the Group into Unity. Then I added NavMesh Surface to help the bot identify which paths it can take. Next, I added navigation points for three houses.   Next is the code section Here is the full code: https://www.notion.so/saibase/Task-3-Group-Assignment-2-30-274fd41960338089b801c3b4436f1aac?source=copy_link#2defd419603380b5b29ae8af7b772377 Presentation: Reflection: In Task 3, I learned how to use face recognition to detect faces and then control a bot in Unity to navigate to other people's rooms. I found this process quite interesting. For example, the default face count is 0; when we recognize a text_Pro value of 0, navigation should occur. However, for demonstration purposes, we skipped recording faces with a ...

 Final Project Todo: Processing: We first went to purchase plastic sheets and some essential materials, then set about assembling them. I shall commence by completing my section. My design comprises an entry system featuring three principal components: the HC-SR04 ultrasonic sensor, the SG90 servo motor, and a buzzer. My approach involves using an HC-SR04 ultrasonic sensor to control door access upon entry, or alternatively enabling voice recognition for door opening. Once inside, voice recognition can be employed to activate voice commands and subsequently deactivate them. Afterwards, I tidied up the wiring and affixed it to the plastic board, then fitted it to my model. Click here to view the code: https://www.notion.so/saibase/Final-Project-30-274fd4196033804cbdc0e80e70d0d63a?source=copy_link Individual presentation: This is the part I made myself. Group Presentation:

CV&NLP Task 2 Todo: Processing: I initially constructed my home model within Blender, using an image of a Scandinavian-style house I found online as my reference. Plan Blender Model After creating the model, I exported it and imported it into Unity, thus establishing the base. The next step is to import the speech recognition plugin (Whisper) into Unity. Then, after adding our floor, the voice-controlled robot will automatically navigate its walking route. I have added navigation waypoints to facilitate the bot locating the position. Next, I added several lights, each in a different room. I set three colours: white, green, and red, with white as the default. Next up is my demonstration video.     Reflection: During the course of this task assignment, I gained an understanding of how NLP operates. It proved less daunting than anticipated. The most challenging aspect of this project was undoubtedly troubleshooting the code bugs that arose, though the debugging process itsel...

Task 1 Case Study  Todo: Processing: Case 1:  The Smart Hub Core Function: Serve as the hub for interaction, communication, and control within the home. Natural Language Processing: Users can control all connected smart devices, make video calls, look up information, or set reminders using voice commands. Computer Vision: The built-in camera uses facial recognition to display personalised information (such as calendars and to-do lists) for different family members. During video calls, the camera automatically tracks people to keep them centred in the frame. It also recognis es gestures, such as raising a hand to pause music. Computer Vision and Natural Language Processing:  Personalised proactive interaction. When you enter the living room, CV recognises your identity, and the screen proactively displays your schedule; you can use NLP to ask, “What are the details of my first meeting today?” Spatial Design: It transforms the traditional living room layout into a hu...