edge2ai_pred_maint | Predictive Maintenance at Edge

 by   SuperEllipse Jupyter Notebook Version: Current License: No License

kandi X-RAY | edge2ai_pred_maint Summary

kandi X-RAY | edge2ai_pred_maint Summary

edge2ai_pred_maint is a Jupyter Notebook library typically used in Edge Computing applications. edge2ai_pred_maint has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Predictive Maintenance at the Edge. Traditional computing architecture based predictive analytics engine relies on the model training and serving computations hosted on on-prem, cloud or hybrid infrastructure. The engine is invoked by a remote asset over a network with data on which the engine provides the inferences. This to and fro information exchange between the data generating asset and the predictive engine suffers from latency, potential dependence on network bandwidth and stability. As connected devices proliferate in Industrial assets, there will be use cases of local computation on these devices driven by limited or intermittent network connectivity and need for real-time decision making. These devises at the edge may additionally have specific data processing challenges as driven by constraints in power consumption, compute, memory and storage capabilities.
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              edge2ai_pred_maint has a low active ecosystem.
              It has 1 star(s) with 0 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              edge2ai_pred_maint has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of edge2ai_pred_maint is current.

            kandi-Quality Quality

              edge2ai_pred_maint has no bugs reported.

            kandi-Security Security

              edge2ai_pred_maint has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              edge2ai_pred_maint does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              edge2ai_pred_maint releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.

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            edge2ai_pred_maint Key Features

            No Key Features are available at this moment for edge2ai_pred_maint.

            edge2ai_pred_maint Examples and Code Snippets

            No Code Snippets are available at this moment for edge2ai_pred_maint.

            Community Discussions

            QUESTION

            Skooma input validator
            Asked 2022-Feb-03 at 15:35

            I was given a task to implement an input validator with the Skooma library https://github.com/bobfp/skooma#validators

            The general concept is pretty clear, but for some inputs I have a list of "legal" words, and I have zero clue on how to implement the validation for this case. Hence why I came here, I wanted to ask if you know any examples / projects that used this library? I googled but didn't find anything. Of if you have any other tipps just let me know! 🙂 This is the example:

            my schema:

            ...

            ANSWER

            Answered 2022-Jan-31 at 00:05

            You need a custom validator function, here's an example:

            Source https://stackoverflow.com/questions/70913797

            QUESTION

            How do I create a Near Edge computing system? (Send sensor data with Raspberry Pi/DHT11 sensor)
            Asked 2021-Jan-22 at 10:01

            I am working on edge computing for IoT applications and expected to create a system that acts as a near edge computer with the use of a raspberry pi hooked up to a dht11 sensor. How do I send this data over to a computer that is at the edge? Ideally I want to use my PC as this device but I have no clue how to send this data over in real time.

            So far I have created the circuit and can view the temperature and humidity readings on the raspberry pi in python. Unsure of what the next steps are - I don't want to send this data over to the cloud just yet.

            Side note: I believe i may be missing knowledge regarding this but is the raspberry pi an edge device because it is hooked up to the sensor directly?

            Any help is greatly appreciated.

            ...

            ANSWER

            Answered 2021-Jan-22 at 10:01

            You need to think this through a bit more. What will you do with the temperature and humidity data that you receive?

            For example, if you're just experimenting and want to just see the readings in a console on your PC, you can use netcat to send the console output of your Python program from the RPi to PC. No SW development needed, they just have to be in the same network. Not particularly useful for anything else, either.

            Otherwise you need to set up some client-server solution between the RPi and your PC. There's a ton of possible solutions, all depending on what you plan to do with the data. You can use MQTT, HTTP, a straight database connection (MySQL, PostgreSQL), etc. You have to supply both sides of the connection. The Python code on client side which connects and sends data; and the server side thing that accepts the samples and stores them somewhere. Plus all the networking, authentication etc.

            Or you can just download the Python client libraries for your favourite cloud solution and set that up according to a tutorial. TBH, this sounds a lot less work to me.

            Source https://stackoverflow.com/questions/65835920

            QUESTION

            What is the time complexity of this peudo code?
            Asked 2020-Jun-21 at 12:16

            I don't have a lot of knowledge computing the complexity. Can you help estimate the complexity of the following pseudo-codes?

            Algorithm 1:

            ...

            ANSWER

            Answered 2020-Jun-21 at 11:50
            Algorithm1
            1. The algorithm1 will first perform simple multiplication and addition on vectors. Assuming that it loops from start to end on each vector and performs some calculations, the number of iterations made would be 3*N which would be considered O(N)

            Source https://stackoverflow.com/questions/62497868

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install edge2ai_pred_maint

            Launch a New CML Project
            Create a pull request for this project from github
            Launch a new Project Session with default parameters
            run the following command by launching Terminal to setup the necessary Python packages
            Walk through the Predictive Maintenance.ipynb for injestion, exploration, training and model persistence
            Alternatively, you can just train the model directly by executing running hte file model_training.py
            Check whether the model has been persisted in model folder.
            Once the model is saved, you can check if the model is serving inferences for a sample record by executing the following command
            You should see the response as below. The Response interpretation is the Remaining Useful Life (RUL) predicted is 118 Time cycles. The machine is not predicted to Fail. The probability of failure is 12%

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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          • HTTPS

            https://github.com/SuperEllipse/edge2ai_pred_maint.git

          • CLI

            gh repo clone SuperEllipse/edge2ai_pred_maint

          • sshUrl

            git@github.com:SuperEllipse/edge2ai_pred_maint.git

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