Abstract
Deepstream 360 D Smart Parking Application is an open-source Internet of Things (IoT) project. Describes the full end to end smart parking application that is available with DeepStream 5.0. The perception capabilities of a DeepStream application can now seamlessly be augmented with data analytics capabilities to build complete solutions, offering rich data dashboards for actionable insights. This bridging of DeepStream’s perception capabilities with data analytics frameworks is particularly useful for applications requiring long term trend analytics, global situational awareness, and forensic analysis. It is built using JavaScript. The complete source code is publicly available on GitHub under the MIT License, making it a useful reference for students building an Internet of Things (IoT) mini project or final-year project.
1. Introduction
The perception capabilities of a DeepStream application can now seamlessly be augmented with data analytics capabilities to build complete solutions, offering rich data dashboards for actionable insights. This bridging of DeepStream’s perception capabilities with data analytics frameworks is particularly useful for applications requiring long term trend analytics, global situational awareness, and forensic analysis. This also allows leveraging major Internet of Things (IOT) services as the infrastructure backbone.
The data analytics backbone is connected to DeepStream applications through a distributed messaging fabric. DeepStream 5.0 offers two new plugins, gstnvmsgconv and gstnvmsgbroker, to transform and connect to various messaging protocols. The protocol supported in this release is Kafka.
2. Objective
Describes the full end to end smart parking application that is available with DeepStream 5.0
This project demonstrates how JavaScript can be applied to a real-world Internet of Things (IoT) problem.
4. Technology Stack
5. System Requirements
General requirements for this technology stack — check the README for exact versions.
- Node.js (LTS) and npm
- A modern web browser
- VS Code or any code editor
- Git (to clone the repository)
6. Installation & Setup
git clone https://github.com/NVIDIA-AI-IOT/deepstream_360_d_smart_parking_application.git
cd deepstream_360_d_smart_parking_application- Analytics Server: Check the README inside analytics_server_docker directory and follow the steps to start the docker containers.
- Perception Server: Check the README inside perception_docker directory and follow the steps to start the docker container.
- Application note
Full setup instructions are in the project README.
7. Future Enhancements
Suggested extensions you can add to make this your own project.
- Add a mobile dashboard using Blynk or Firebase
- Store readings in a cloud database for history charts
- Add alerts via SMS / Telegram when thresholds are crossed
8. Viva / Review Questions
Common questions examiners ask for projects in this domain.
- Which microcontroller / board and sensors are used and why?
- How does the device send data (Wi-Fi, MQTT, HTTP, Bluetooth)?
- Where is the sensor data stored and visualised?
- How is power consumption managed?
- How would you secure the device and its communication?
9. Source Code & License
This project is developed by NVIDIA-AI-IOT and published on GitHub under the MIT License. Please follow the license terms and credit the original author when you use or modify this code.
Want to build this as your internship project?
Work on an Internet of Things (IoT) project like this with mentor guidance, weekly reviews and an internship certificate from Training Trains, Erode — online or offline.
Apply for Internet of Things (IoT) Internship