文件列表:

.vscode/ (0, 2023-12-01)
.vscode/settings.json (80, 2023-12-01)
Analytics_Implementation/ (0, 2023-12-01)
Analytics_Implementation/Fall_2023/ (0, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/ (0, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/09-23-23/ (0, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/09-23-23/Circular Sander Data - ACC X.csv (9027, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/09-23-23/Circular Sander Data - ACC Y.csv (9055, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/09-23-23/Circular Sander Data - ACC Z.csv (8996, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/09-23-23/Circular Sander Data - Pitch.csv (8692, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/09-23-23/Circular Sander Data - Roll.csv (8412, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/09-23-23/Circular Sander Data - raw_convert.csv (44046, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/10-27-23-MDF.csv (7932, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/10-27-23-Pine-And-MDF.csv (20444, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/10-27-23-Pine.csv (12579, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/10-31-23-Corrected.csv (48435, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/10-31-23-Disc-Sander.csv (46731, 2023-12-01)
Analytics_Implementation/Fall_2023/Fall_2023_Data_Collection_Data_Sets/desktop.ini (201, 2023-12-01)
BeagleBone/ (0, 2023-12-01)
BeagleBone/serialInit.py (834, 2023-12-01)
BeagleBone/serialToAWS.py (1600, 2023-12-01)
Housing_Implementation/ (0, 2023-12-01)
Housing_Implementation/Fall_2023/ (0, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/ (0, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Drawings/ (0, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Drawings/Bottom.PNG (47076, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Drawings/Middle.SLDDRW (568200, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Drawings/Screw_Assembly.PNG (40969, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Drawings/Screw_Assembly.SLDDRW (375251, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Drawings/Top.PNG (43175, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Model_References/ (0, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Model_References/90592A095_Steel Hex Nut.SLDPRT (436885, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Model_References/91290A268_Alloy Steel Socket Head Screw.SLDPRT (731819, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Model_References/BEAGLEBONE_BLACK.SLDPRT (8616945, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/STL_Files/ (0, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/STL_Files/Screw_Bottom.STL (320284, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/STL_Files/Screw_Top.STL (145784, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Screw_Assembly.STEP (20869123, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Solidworks_2023_Files/ (0, 2023-12-01)
Housing_Implementation/Fall_2023/IN-USE-Fastener_Housing/Solidworks_2023_Files/Bottom.SLDPRT (346265, 2023-12-01)
... ...

 # [Makerspace IoT (MSIoT)](https://github.com/GeorgiaTech-DDI/makerspace_iot/blob/master/https://github.com/GeorgiaTech-DDI/makerspace_iot/wiki) Makerspace IoT is a sub-project of the Smart^3 Makerspaces Vertically Integrated Project, aiming to digitalize and provide actionable insights for machines in the Flowers Invention Studio. This is achieved using sensors which continuously collect data on various parameters (current, vibration, temperature) for a machine. The project aims to create a one-of-a-kind low-cost, scalable IoT infrastructure which aids in the **predictive maintenance** of the machinery. This wiki provides live documentation of the resources utilized in the project. ## [Introduction and Onboarding](https://github.com/GeorgiaTech-DDI/makerspace_iot/blob/master/https://github.com/GeorgiaTech-DDI/makerspace_iot/wiki/Introduction-&-Onboarding-for-MSIoT) *What impact does this project create? How does this contribute to the existing IoT and predictive maintenance research?* **Aim of the project**
Enable data collection for various machine parameters in Flower Invention Studio. **Research gap identified**
After going through various research papers we realised there was no paper which holistically combines principles of mechanical, electrical, electronics and computer science to setup predictive maintenance .............. **Work done:**
We have made an IoT infrastructure which utilizes sensors to gather data on various machine parameters like current, vibration, temperature etc. These machine parameters are constantly measured and stored in a cloud warehouse. **Impact created**
This data stored can be utilized in 2 ways:- 1. Live visualization: An app can be created that displays a live dashboard showcasing real-time values of the current, vibration and temperature. This can be utilized in small-medium sized industrial setups which till now have not modernized their machinery. The low cost of our infrastructure can help bring these sectors online. 2. **Predictive maintenance:** As discussed in the *research gap* part, in the present scenario only industries with high capital are able to utilize sensor-based predictive maintenance techniques for their machines. **Result**
After this research project, we will have documentation that talks about an end-to-end method to enable predictive maintenance for any machine in the industry, from **sensor selection -> Circuitry -> Cloud infrastructure -> Data collection procedures -> Data manipulation and insights**. After reading the documentation anyone can set up a predictive maintenance infrastructure without requiring any prior experience with the same. [**Click here**](https://github.com/GeorgiaTech-DDI/makerspace_iot/blob/master/https://github.com/GeorgiaTech-DDI/makerspace_iot/wiki/Introduction-&-Onboarding-for-MSIoT) **to get detailed info about project goals, teams, hardware & software used and much more..!** ## [Documentation](https://github.com/GeorgiaTech-DDI/makerspace_iot/blob/master/https://github.com/GeorgiaTech-DDI/makerspace_iot/wiki) MSIoT documents, setups, and details on progress.  ## Point Of Contacts **MSIoT Lead**
Gate Tangchartsiri (Computer Engineer Undergraduate)
Atlanta, Georgia
gate.tang@gatech.edu
www.linkedin.com/in/gate-tangchartsiri/
**Team Lead - Analytics**
Aditya Jarial (Mechanical Engineering Researcher at Georgia Tech)
Gurugram, India
mr.adityasingh99@gmail.com
www.linkedin.com/in/aditya-jarial
## Additional Information [MAC Address Indentifier](https://github.com/GeorgiaTech-DDI/makerspace_iot/blob/master/https://randomnerdtutorials.com/get-change-esp32-esp8266-mac-address-arduino/)

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