Unleashing the Power of AI with Telo Drone and Deep Stream

Table of Contents

1. Introduction
2. The Telo Drone: An Indoor Quadcopter
3. Deep Stream: AI Analytics on Jetson Nano
4. Building an AI-Based Application with Telo Drone and Deep Stream
   • Setting up the Hardware
   • Configuring the Telo Drone as a Hotspot
   • Controlling the Drone with Python Code
   • Streaming and Analyzing the Video with Deep Stream
   • Storing and Analyzing the Data with Redis
5. The Cherry Bot: A Food Delivery Robotic Platform
6. Conclusion

🚁 Building AI Applications with Telo Drone and Deep Stream

Introduction

In today's technological era, drones and artificial intelligence (AI) play a significant role in various industries. In this article, we will explore the powerful combination of the Telo Drone and Deep Stream. The Telo Drone is an indoor quadcopter that allows for easy programming using Python, while Deep Stream unlocks the capabilities of AI analytics on the Jetson Nano. By integrating these technologies, we can create innovative AI applications, such as fire detection and autonomous control.

1. The Telo Drone: An Indoor Quadcopter

The Telo Drone is a lightweight indoor quadcopter weighing only 80 grams. It is perfect for experimentation and exploration within a controlled environment. Equipped with a 5-megapixel camera, the Telo Drone captures images and videos, which can then be analyzed using AI algorithms.

The Telo Drone can be controlled using Python scripts, making it an excellent platform for learning and experimentation. By connecting your laptop to the drone, you can control its movements, perform flips, and explore various programming possibilities.

2. Deep Stream: AI Analytics on Jetson Nano

Deep Stream is a powerful AI analytics tool that transforms the Jetson Nano into an AI computer with advanced analytics capabilities. Deep Stream provides GPU support, enabling the execution of complex AI algorithms directly on the Jetson Nano.

With Deep Stream, you can leverage the impressive processing power of the Jetson Nano for object detection, Image Recognition, and more. It comes with a rich software stack, including libraries like TensorRT, Vision Works, and OpenCV, making it easy to develop AI applications on the Jetson Nano.

3. Building an AI-Based Application with Telo Drone and Deep Stream

To harness the full potential of the Telo Drone and Deep Stream, let's dive into the process of building an AI-based application that utilizes both technologies. The following steps Outline how to set up the hardware, configure the drone, control it with Python code, stream and analyze the video with Deep Stream, and store the data with Redis.

• Setting up the Hardware: Begin by powering on the Telo Drone and configuring it as a hotspot. Connect a Jetson Nano to the drone, either via Wi-Fi or a USB connection.

• Controlling the Drone with Python Code: Write Python code to control the Telo Drone's movements, such as takeoff, landing, moving forward, rotating, and more. The Telo Drone's lightweight design and Python compatibility make it an ideal platform for experimentation.

• Streaming and Analyzing the Video with Deep Stream: Use Deep Stream's powerful AI analytics capabilities to analyze the video stream captured by the Telo Drone. Deep Stream supports various AI models and provides real-time object detection, recognition, and analytics. Stream the video to an RTSP endpoint for easy viewing and further analysis.

• Storing and Analyzing the Data with Redis: Use Redis, a high-performance in-memory data structure store, to store the video frames and perform further analytics. Redis supports real-time data ingestion and querying, making it an excellent choice for storing and analyzing the continuous stream of data generated by the Telo Drone and Deep Stream.

4. The Cherry Bot: A Food Delivery Robotic Platform

Another exciting project worth mentioning is the Cherry Bot, a food delivery robotic platform. This AI-based platform utilizes the Jetson Nano, AI algorithms, and various hardware components to create an autonomous food delivery system. By integrating AI analytics, sensors, and GPS modules, the Cherry Bot can navigate and deliver food within a fixed area, making it an innovative solution for universities, residential areas, and other communities.

Conclusion

In this article, we've explored the possibilities of building AI applications using the Telo Drone and Deep Stream technologies. The combination of these hardware and software tools enables developers to create innovative solutions in various domains, including fire detection, remote monitoring, object recognition, and autonomous control. Whether it's capturing aerial footage or delivering food, the Telo Drone and Deep Stream provide endless possibilities for AI experimentation and application development.

By fostering collaboration and leveraging the power of these technologies, we can unlock new levels of innovation and Shape the future of AI and robotics.

Resources:

• Telo Drone: https://www.ryzerobotics.com/tello
• Deep Stream: https://developer.nvidia.com/deepstream-sdk
• Redis: https://redis.io/
• Cherry Bot Project: https://cherryboard.collabnix.com/