Smart Ai Gloves
About the project
AI-based hand gloves, gives you a super power to control any devices with motions.
Project info
Difficulty: Moderate
Platforms: Avnet, NXP, Raspberry Pi
Estimated time: 7 days
License: GNU General Public License, version 3 or later (GPL3+)
Items used in this project
Hardware components
Avnet SmartEdge Agile Brainium | x 1 | ||
Raspberry Pi Zero | x 1 | ||
NXP Rapid IoT Prototyping Kit | x 1 | ||
Fan Kit, 120 mm Fan | x 1 | ||
LED Light Bulb, Frosted GLS | x 1 | ||
NXP Kinetis KW41Z | x 3 | ||
Golf Gloves | x 1 | ||
RC car | x 1 |
View all
Story
It was my old thought of making some gadgets of super heroes like Iron Man. After analyzing the Avnet SmartEdge device and Brainium cloud, got some idea to make such kind of wearable gloves. Controlling devices in gesture manner.
I received the Avnet kit, the first thing I explored about the Branium cloud and basic features. I have done very basic level project here.
Followed by my basic demo, I started this project activity. I listed out the motions required in my project. Then with AI Studio I reordered many motions and created modules. Started testing with mobile app initially. Then later I started using Brainium app in Raspberry Pi.
Motions Set
Motions Set
Brainium APP on Raspberry pi zero
Brainium APP on Raspberry pi zero
Also integrated the Rapid IoT kit for thread networking and display. Its talks with all the thread end nodes and controls it.
Rapid IoT Kit
Rapid IoT Kit
The Main Features of AI Gloves:1. Unlocking by drawing pattern
2. Light ON/OFF
3. Fan speed control
4. Gesture car control
5. Driver style analyzing in real-time
Blocks:
Python is used to detect the motions/alerts from Brainum cloud using MQTT services. Also it process the motion types then send commands to Rapid IoT kit via UART. Rapid IoT takes the action via Thread. Due to cloud based processing, it will take 3 to 5sec to update the results. But still Brainuim performed well overall.
Avnet SmartEdge device has other inbuilt sensors like magnetic, PIR, accelerator sensors which helps in the driver style analyzing, where the driving information can be used to automate or learning purposes in autonomous car industries.
There are some more demos I have planned in future with this all sensors.
Python MQTT
Python MQTT
The working demo is here:
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