Human Detection Alarm System with Raspberry Pi AI Kit + Maker Pi PICO

Cytron Technologies
19 Jul 202407:43

TLDRExplore the world of AI and machine learning with the new Raspberry Pi AI Kit, featuring the powerful Hyo 8l AI accelerator module. This tutorial guides you through creating a human detection alarm system using the Raspberry Pi AI Kit and the Satron Maker Pi Pico. The system detects humans in real-time, triggering audio and visual alerts. Learn how to set up the components, configure the server and client codes, and integrate the system for a functional AI project.

Takeaways

  • 😀 The Raspberry Pi AI Kit is designed for neural networks, AI, and machine learning on Raspberry Pi 5.
  • 🔍 The kit includes the Hyo 8l AI accelerator module, offering 13 TOPS performance and 3 TOPS/W efficiency.
  • 📈 It outperforms Google Coral TPU in terms of both performance and power efficiency.
  • 🎯 The kit is ideal for edge AI applications due to its high performance and energy efficiency.
  • 🛠️ The satron maker Pi Pico adds features like an SD card slot, audio jack, and RGB LEDs to the Raspberry Pi.
  • 👥 The project aims to create a human detection alarm system using the Raspberry Pi AI Kit and maker Pi Pico.
  • 📹 The system uses a Raspberry Pi camera for visual input, which is processed by the AI kit for real-time object detection.
  • 💡 Upon detecting a person, the system triggers audio and visual notifications through a speaker and RGB LEDs.
  • 🛠️ The system architecture involves the Raspberry Pi 5 running the AI kit, the camera module for video feed, and the maker Pi Pico for alerts.
  • 📝 The background processing script in bash monitors object detection and updates a file that the server code monitors.
  • 💻 The server code in Python listens for object detection results and sends notifications to the client code on the maker Pi Pico.

Q & A

  • What is the purpose of the Raspberry Pi AI Kit mentioned in the transcript?

    -The Raspberry Pi AI Kit is designed to enable users to explore neural networks, AI, and machine learning on a Raspberry Pi. It integrates high-performance, power-efficient inferencing for various applications.

  • What is the performance capability of the Hyo 8l AI accelerator module included in the AI Kit?

    -The Hyo 8l AI accelerator module delivers 13 Terra operations per second and is claimed to be efficient at three tops per watt.

  • How does the performance of the Hyo 8l AI accelerator module compare to Google Coral TPU?

    -The Hyo 8l AI accelerator module offers higher performance with 13 Tops compared to Google Coral TPU's 4 Tops, and it is more energy efficient at three tops per watt compared to the TPU's two tops per watt.

  • What additional features does the maker Pico board bring to the Raspberry Pi?

    -The maker Pico board adds features like a built-in SD card slot for storage, a 3.5 mm audio jack for external speakers, and built-in RGB LEDs to the Raspberry Pi.

  • What is the main project described in the transcript?

    -The main project described is a human detection alarm system that uses the Raspberry Pi AI Kit and maker Pico to detect a person and trigger audio and visual notifications.

  • What components are required to build the human detection alarm system as described?

    -The components required include a Raspberry Pi 5, the Raspberry Pi AI Kit, a Raspberry Pi camera for visual input, the maker Pico, a speaker for audio notifications, an SD card for audio storage, and optionally an NVMe SSD with a USB to M.2 adapter for faster operations.

  • How does the system architecture for the human notification system work?

    -The system architecture involves the Raspberry Pi 5 running the AI Kit for real-time object detection using the Hyo 8l AI accelerator with YOLOv6. The Raspberry Pi camera module 3 captures video feed, which is processed by the AI kit. Upon detecting a person, the server on the Raspberry Pi 5 sends a notification to the maker Pico, which then triggers audio and visual alerts.

  • What is the role of the background processing script in the system?

    -The background processing script runs the object detection model and monitors its output for person detections. When a person is detected, it updates a file that the server code monitors.

  • How does the server code on the Raspberry Pi 5 interact with the object detection results?

    -The server code continuously monitors the object detection results from the camera feed. When a person is detected, it sends a notification to the client code running on the maker Pico.

  • What does the client code running on the maker Pico do when it receives a notification from the server?

    -Upon receiving a notification from the server that a person has been detected, the client code on the maker Pico lights up the RGB LEDs and plays an audio alert stored on the SD card.

  • What are the steps to set up the human detection alarm system as per the transcript?

    -The steps include inserting the SD card into the maker Pico, connecting the speaker, attaching the Raspberry Pi camera module to the Raspberry Pi 5, connecting the maker Pico to the Raspberry Pi 5 via USB, cloning the repository with necessary project files, configuring the client and server codes, and running the system.

Outlines

00:00

🤖 Introduction to Raspberry Pi AI Kit and Project Overview

The paragraph introduces the new Raspberry Pi AI kit, designed for integrating AI and machine learning with a Raspberry Pi 5. It highlights the kit's collaboration with Hyo and the inclusion of the Hyo 8l AI accelerator module, which offers 13 Terra operations per second at an efficiency of 3 TOPS per watt. This is compared to the Google Coral TPU, which provides 4 TOPS at 2 TOPS per watt. The paragraph also mentions the Pico W board with its additional features like an SD card slot, audio jack, and RGB LEDs. The project's aim is to create a human notification system using these components, which will detect a person and trigger audio and visual alerts. The system architecture is briefly described, involving the Raspberry Pi 5 running the AI kit for real-time object detection, the Raspberry Pi camera for video input, and the Pico W for notifications. The paragraph ends with an introduction to the components needed for the project and a preview of the system's setup.

05:03

🛠️ Setting Up the Human Notification System

This paragraph provides a step-by-step guide to setting up the human notification system. It details the process of connecting the Raspberry Pi camera module to the Raspberry Pi 5, attaching the maker Pi Pico, and cloning the repository for the project files. The instructions include configuring the client-side code on the Raspberry Pi Pico W to communicate with the server, which involves updating the Wi-Fi network details and server IP address. The server-side setup is also explained, including making the camera monitor script executable and starting the server to handle object detection and notifications. The paragraph concludes with the activation of the system, demonstrating its capability to detect a person and trigger notifications through RGB LEDs and audio alerts in real-time. The project showcases the integration of AI capabilities with enhanced hardware features, making it accessible and powerful.

Mindmap

Keywords

💡Raspberry Pi AI Kit

The Raspberry Pi AI Kit is a specialized hardware and software bundle designed to facilitate the development of artificial intelligence applications on the Raspberry Pi platform. In the video, this kit is highlighted as a gateway to the world of neural networks, AI, and machine learning, emphasizing its role in integrating high-performance inferencing capabilities into various applications. The kit features the Hyo 8l AI accelerator module, which is central to the project's ability to detect and respond to human presence.

💡Hyo 8l AI Accelerator

The Hyo 8l AI Accelerator is a component of the Raspberry Pi AI Kit that significantly enhances the device's ability to perform AI-related tasks. It is capable of delivering 13 Terra operations per second, which is a measure of its computational power. This module is crucial for the video's project as it enables real-time object detection, particularly for identifying human presence, with high efficiency and performance.

💡Google Coral TPU

The Google Coral TPU is a comparison point mentioned in the script to illustrate the performance and efficiency of the Hyo 8l AI Accelerator. It is a hardware accelerator designed to run TensorFlow Lite models and is known for its use in previous generations of Raspberry Pi devices. The script contrasts the Coral TPU's 4 Tops performance with the Hyo 8l's 13 Tops, highlighting the latter's superior capabilities for edge AI applications.

💡Maker Pi Pico

The Maker Pi Pico is an add-on board for the Raspberry Pi that simplifies digital projects by providing additional features. It includes an SD card slot for storage, a 3.5 mm audio jack for connecting external speakers, and built-in RGB LEDs for visual notifications. In the video, the Maker Pi Pico is used to trigger audio and visual alerts when a person is detected by the AI system, demonstrating its utility in creating a comprehensive human detection alarm system.

💡Real-time Object Detection

Real-time object detection is a process where the system continuously analyzes video feeds to identify and respond to specific objects or entities, in this case, humans. The video describes how the AI kit, using the Hyo 8l AI accelerator and YOLOv6, performs this task to detect human presence. This capability is essential for the human detection alarm system, as it allows for immediate and accurate responses to the presence of a person.

💡YOLOv6

YOLOv6, or You Only Look Once version 6, is an advanced object detection algorithm used in the video's project for real-time detection of humans. It is known for its speed and accuracy in processing video feeds and identifying objects. In the context of the video, YOLOv6 is utilized by the Raspberry Pi AI Kit to detect humans, which is a critical component of the human detection alarm system being demonstrated.

💡Server Code

The server code, written in Python, is a part of the system that monitors the output from the object detection model and sends notifications when a person is detected. It is responsible for handling the communication between the AI kit's detection capabilities and the Maker Pi Pico's alert system. The server code is integral to the video's project as it bridges the detection of human presence with the subsequent alert mechanisms.

💡Client Code

Client code, running on the Raspberry Pi Pico W, is responsible for receiving notifications from the server and triggering the appropriate responses, such as lighting up the RGB LEDs and playing an audio alert. This code is written in CircuitPython and is crucial for the video's project as it executes the final step in the alarm system's operation, ensuring that when a person is detected, the system responds with both visual and audio notifications.

💡RGB LEDs

RGB LEDs are used in the video's project for visual notifications. They can display a variety of colors and are controlled by the Maker Pi Pico to light up in response to the detection of a person. The use of RGB LEDs adds a visual element to the alarm system, providing immediate and clear feedback that a person has been detected, which is a key feature of the human detection alarm system described in the video.

💡Audio Alert

An audio alert is a sound played to notify users of an event or action, such as the detection of a person in the video's project. The audio alert is stored on an SD card and played through an external speaker when the server code detects a person. This auditory feedback is an essential part of the alarm system, ensuring that the presence of a person is communicated effectively and immediately.

Highlights

The Raspberry Pi AI Kit is a new tool for diving into AI and machine learning on Raspberry Pi.

It integrates with the Hyo 8l AI accelerator module for high performance inferencing.

The Hyo 8l module offers 13 Terra operations per second and is energy efficient at 3 TOPS/W.

Compared to Google Coral TPU, the AI Kit provides better performance and energy efficiency.

The kit is suitable for Edge AI applications due to its superior choice in performance and energy efficiency.

The Pico W board on the satron maker Pi Pico adds features like an SD card slot and RGB LEDs.

The project is a human detection system that triggers audio and visual notifications.

Components needed include a Raspberry Pi 5, AI Kit, camera, speaker, SD card, and optionally an NVMe SSD.

The system architecture involves the Raspberry Pi 5 running the AI kit for real-time object detection.

The Raspberry Pi camera module 3 captures video feed processed by the AI kit to detect humans.

When a person is detected, the server on the Raspberry Pi 5 sends a notification to the satron maker Pi Pico.

The Pi Pico triggers audio and visual alerts using a speaker and built-in RGB LEDs.

The background processing script is written in bash and monitors for person detections.

The server code in Python listens for object detection results and sends notifications to the client.

The client code on the Raspberry Pi Pico W is written in circuit python and handles Wi-Fi and notifications.

The system is set up by inserting an SD card, connecting a speaker, and attaching the camera module.

Detailed instructions and project files are available on the satron tutorial page.

The system is ready to detect a person and trigger notifications through the RGB LED and audio interface.

The project demonstrates the integration of advanced AI capabilities with enhanced hardware features.

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