Home automation using artificial intelligence
- Projects 4
- Followers 108
Folsom, CA, USA
I've got request from my client to build a motion simulator of car racing game. To be honest I never build even learn about motion simulator. Collect a lot of information from google and youtube as references to learn. Basically we can get 3D Motion Data from almost racing simulator games. I join the XSimulator.net community to get a lot of useful information and tutorial about Motion Simulator.
I use 2 PCs for this project. One as Gaming PC with high-specs and One as Game Controller that connect to Genuino101 via USB. Both PC connected via Crossed Ethernet Cable. Gaming PC Specs: Intel i7-6700 3.4GHz, 32GB DDR4, SSD 250GB, GTX1070 Video card, ASUS H170 Pro Gaming Motherboard. Game Controller PC Specs: Lenovo ThinkCentre M93p Mini PC, Intel i5-2.9GHz, 8GB DDR3, SSD250GB
I start from design sketch, then make a scaled model using 3D printing for learning the mechanism works and test the code and interconnection data from 2 pc. Continue drawing in 3D CAD to get detail size/dimension of metal parts.
Then start prepare the construction and build using MIG / CO Welding. I use Wiper Motor for Mercedes Benz 300E car as the actuator for motion simulator. And for driver, I use 43A BTS7960 DC Motor Driver and 30A 12V Switching Power Supply.
For Gaming Gear, I use Thrustmaster T500RS Steering Wheel and Pedals + Gear Shift. For Sound System, I use Razer Leviathan 5.1 Surround Sound Bar Dolby Speaker. The subwoofer placed on rig-base under the seat. I use 3 Samsung Curve 24" Monitor driven by GTX1070 multi display Video Adapter.
For game itself I choose Asseta Corsa and Project Cars. This project developed in two months.
Home automation using artificial intelligence
Just finished the hombase device for elder care facilities. This device eliminates the need for all the BLE hubs required.
This is about online shopping. Here, the user gets a 3D viewpoint of the product which he/she wants to purchase. After getting a feel, the user is able to make a relevant decision considering his/her choice and accordingly the product will be bought.
I'm Akshay Pradeep now I am doing Diploma in Electronics Engineering in Govt. Polytechnic Chelakkara
In recent years, research over information exchange between vehicles has been growing, with the goal to improve safety and efficiency in traffic. This project describes the development of a multi-agent system for simulation of connected vehicles in road crossings, in order to remove the need for traffic lights. The system was developed using the C# programming language and Boris.NET platform for communication between agents. The user can specify the desired environments using JSON files which are read at the simulation startup. A 2D graphical interface was also created to view the simulation, so that it can follow an agent or stay at a map position.
This work presents the development of a prototype for the recognition of universal facial expressions. This technic provides an alternative way of gathering data from the user, being able for usage as an input way for information systems. For faces detection and extraction of their characteristics technics of Computer Vision and Digital Image Processing are employed, implemented by the dlib library with Intel RealSense. The classification into facial expressions is performed by an Artificial Neural Network, of the multilayer perceptron kind.
TASS PVL is a sister project to the original TASS Hub project. As with TASS Hub, TASS PVL is a local server which homes an IoT connected A.I. powered by the Intel® Computer Vision SDK Beta. The hub can connect to multiple IP cameras and two Realsense cameras. First, the program detects if there is a face, or faces, present in the frames, and if so passes the frames through the trained model to determine whether the face is a known person or an intruder. In the event of a known person or intruder, the server communicates with the IoT JumpWay which executes the relevant commands that set by rules, for instance, controlling other devices on the network or raising alarms in applications etc.
TASS PVL uses the following Intel technologies:
The IoT connectivity is managed by the TechBubble IoT JumpWay, the TechBubble Technologies IoT PaaS which primarily, at this point, uses secure MQTT protocol. Rules can be set up that can be triggered by sensor values/warning messages/device status messages and identified known people or intruder alerts. These rules allow connected devices to interact with each other autonomously, providing an automated smart home/business environment.
TASS PVL uses the Intel Computer Vision SDK Beta to provide the system with Artificial Intelligence. For other uses of A.I. used in the sister project TASS PVL, follow this link.
The IntelliLan Management Console/Applications are essentially IoT JumpWay applications, capable of controlling all IntelliLan devices on their network and communicating with the IoT JumpWay. Users can use the console and manage their devices using their voice which is powered by TIA, an A.I. agent developed to assist home and business owners to use TechBubble web and IoT systems.
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I'm Information Technology undergrad at Maharaja Agrasen Institute of Technology in India. I am a Backend and Mobile developer specialising in Node, Android, Python and iOS. I've also created some Augmented Reality projects in past with ARKit and Vuforia. My latest research is in the field of Image Processing, in which I created an IOT based Rover which follows a required path without any errors. I used Edge Detection technique in it as well. I am also very interested in deep learning and NLP. I've worked with Tensorflow and Keras. I'm excited to know the what projects you've been working on in those fields!
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