I need a solution architect to design a comprehensive system for my machine learning project. The successful candidate will have experience in architecting desktop client that integrates with other microservices running on the client side, such as machine learning model, data syncing to cloud services, process schedulers to pass in data from different services using recommended protocols (API, GRPC or event driven pipeline) to achieve analytical outcomes.
The project involves:
- RTSP video streams analysis using machine learning models
- Generating visuals (graphs/charts) of data collected with filtration of historical data from a database
- Syncing collected data to a cloud BI application
- Reporting modules to generate automated daily, weekly, monthly reports
- Integration with existing systems
What are the deliverables of this project from you?
We are already a team of machine learning developers, electron js desktop developer along with devops engineers. What we are seeking is a detailed solutions guideline to follow to implement for our project. Identify how each component of the system will work out, how it will work together in detailed. For example how machine learning models will communicate with desktop client and where the data will be stored for cloud syncing. What are the methods of retrying in case a sync is failed? These are the directions to be thought of and create a detailed document with diagram and explanation for each team member of ours to work on.
What the final product looks like?
1. End user installs a desktop application, connects any camera he has through RTSP protocol.
2. The machine learning team develops AI models to analyze these RTSP streams to provide visual insights such as, people emotion, demographics, counting of people, crowd management alerts.
3. The data collected is visualized in desktop electron js application as graphs/charts.
4. The user has ability to automate report generation and sent through emails.
5. The data collected is sent to a cloud application which is a BI tool to visualize the data in different formats/ filtrations.
In addition, understanding the design of real-time streaming protocol (RTSP) systems is also advantageous. The detailed technical solution is the main goal of this project. The ideal candidate is a highly skilled machine learning engineer who is proficient in developing and incorporating system designs.
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