Smart Parking for Smarter Cities: Building an End-to-End Data Pipeline with Raspberry Pi HMIs, AWS, TensorFlow, and N3uron

Introduction

Urban environments are constantly evolving, and managing traffic flow and parking remains a major challenge. Smart car parking solutions powered by edge computing and AI are emerging as a critical component of successful smart cities. Let’s explore how these solutions contribute to a more efficient and sustainable urban landscape.

  • Reduced Traffic Congestion: Drivers spend a significant amount of time searching for parking, leading to unnecessary congestion.
  • Enhanced Efficiency and Revenue: Smart parking systems automate the parking process, eliminating the need for manual enforcement.
  • Environmental Sustainability: Reduced search times translate to lower fuel consumption and emissions. Smart parking systems can also optimize lighting in parking lots based on occupancy data, further minimizing energy usage.
  • Data-Driven Decision Making: The data collected by smart parking systems provides valuable insights into parking patterns and demand. Cities can leverage this information to optimize parking infrastructure and develop data-driven policies to address congestion and parking availability challenges.

Tech Stack Breakdown

Smart parking systems using TensorFlow Lite for on-device object detection can identify available spots in real-time. This data, published to the AWS cloud and accessed by N3uron on reTerminal devices (located even in remote areas), helps drivers locate open spots quickly, minimizing time spent circling and contributing to smoother traffic flow. Let’s talk bit more about Tech Stack which is related to the Demonstration.

A lightweight version of TensorFlow for on-device inference. A custom object detection model, like EfficientDet or YOLOv5, trained on a car park dataset is deployed on the reTerminal device to identify available parking spots in real-time from the video feed.

The AWS cloud platform acts as a message broker using the MQTT protocol. The reTerminal device publishes the number of available parking spots detected by the TensorFlow Lite model to the AWS cloud.

This Industrial Edge Platform for IIoT & DataOps subscribes to the published data from AWS IoT Core using an MQTT connection. N3uron allows for data visualization through user-friendly dashboards, enabling users to monitor parking slot availability in real-time and analyze trends over time.

Hardware Components

reTerminal

This compact Raspberry Pi-based HMI (Human-Machine Interface) device serves as the core for real-time object detection. It features a touch screen, various connectivity options (WiFi, Bluetooth, USB, etc.), and built-in sensors. In this setup, the reTerminal analyzes the video feed from the Pi camera to count available parking spots.

reTerminal DM

This secondary HMI acts as the data visualization hub. It boasts a larger screen, industrial-grade durability, and diverse communication options (LoraWAN, 4G LTE, etc.) for remote deployments. Here, it displays parking slot availability data received from the reTerminal, potentially even showcasing trends based on the time of day. Imagine this device situated in a building near the car park for convenient monitoring.

The Big Picture

This solution leverages the strengths of various hardware and software components. A reTerminal device equipped with a Pi camera captures video footage of the car park. TensorFlow Lite, deployed on the reTerminal for efficient on-device processing, analyzes the video stream to identify available parking spots. The reTerminal then publishes this data to the AWS cloud using appropriate credentials. In a separate location, another reTerminal DM device subscribes to the published data stream using N3uron, a comprehensive Industrial Edge Platform. N3uron facilitates the creation of a user-friendly interface for visualizing real-time parking slot availability, potentially incorporating historical data to reveal trends in parking occupancy throughout the day.

Seeed Studio’s Raspberry Pi Ecosystem

Seeed Studio has been serving the Raspberry Pi user community since 2013 and took the lead to join the approved reseller and design partner. Since the first version of reTerminal in 2021, we have a series of products including reRouteredge controller series, and last year reTerminal DM, serving creators, makers, enthusiasts, students, engineers, enterprises as well as industries, and every scenario needing Raspberry Pi. 

More Resources

About Author

Leave a Reply

Your email address will not be published. Required fields are marked *

Calendar

April 2024
M T W T F S S
1234567
891011121314
15161718192021
22232425262728
2930