Edge AI Features And Applications

Edge AI camera features and applications

Introduction

Tokay lite is a camera with edge ai features and applications such as night vision, battery-powered, open-sourced, and designed explicitly for software enthusiasts without much hardware expertise.

The device aims to serve as an advanced camera with edge AI processing capabilities that can be used in various applications such as security and surveillance, wildlife monitoring, agriculture technology, and robotics.

Typical Edge AI Features And Applications

Powered by ESP32-S3, the Edge AI camera ensures a secure connection and unparalleled performance while drawing less power than its competitors, thanks to in-house firmware distinctively built to operate in a wide range of use cases.

The chip under the hood is designed for low-power and high-performance applications. Depending on budget scenarios, offering different power options to optimize power consumption and performance further.

In ultra-low power consumption mode, the chip can operate in deep sleep mode with less than 5µA of current drawn and 10ms-1s wake-up time.

In a timelapse mode with 1 hr regular wakeup, a battery with a capacity of 2500 mAh could power the device non-stop for many month.

Edge AI Camera Sensing

Edge AI, equipped with numerous functions, enables it to operate under different conditions.

The camera has an infrared (IR) diodes, enabling night vision. Night vision allows you to capture data even when the amount of light in the environment is low or none.

Detecting the presence and quantity of light (expressed in Lux or Lumen) and detecting motion with its passive IR is also possible.

Configuring the Camera and Integrations

Setting up the camera is easy with a local, no-code configuration interface, which also allows fine-sensor tuning and deep insight into the device’s data.

Integrating automated functions with major IoT and AI platforms like ThingsBoard and Amazon Web Services (AWS) is possible through the interface.

Edge AI’s Specifications

Edge AI has a powerful MCU under the hood. Adding a camera sensor to that equation gives you a perfect tool for developers to enter into machine vision.

TypeCharacteristic
Onboard MCUESP32-S3
Sensor InterfaceDVP
Stock Camera SensorOV2640
Image Size0.3MP/2MP/3MP
Image FormatsRGB, JPEG
Frame RateUp to 15 FPS
Night VisionYes
SensorsLight Sensor, Passive IR (Motion Detection)
ConnectivityWiFi, BLE
Memory8MB Flash, 512 kB + 8MB RAM
SoftwareTF-Lite Micro, esp-dl
InterfacesSPI, UART
Battery ConnectorJST-PH (2mm pitch)
Power FeaturesProgrammable External RTC

Approaching the Camera

As a developer without too much hardware experience, the Edge AI camera is an excellent choice for entering the machine vision world. The device is configured with a local, no-code configuration interface, and it can be integrated with popular IoT and AI platforms like ThingsBoard and AWS.

If you come as more experienced, the Edge AI provides powerful features like real-time image analysis and decision-making on the device itself, fast response times, and the ability to operate in low-light conditions. In addition, the camera’s user-friendly configuration UI makes fine-sensor tuning and deep insight into the device’s data possible.

The learning curve is not really a curve here. Easy-to-use interface and pre-configured integrations allow you to get working data in a simple manner.

Use Cases

As the camera isn’t intended for a single use case, here are a few that might suit you.

1) Security and surveillance

The Edge AI camera can be used for security and surveillance purposes thanks to its night vision capabilities and motion detection sensors. In addition, it can be set up to send alerts to your phone or email when motion is detected, making it an excellent option for monitoring your property.

2) Wildlife monitoring

Monitoring wildlife in a non-intrusive and humane way is essential. Edge AI’s motion detection sensors can capture footage of animals without disturbing them. The camera’s night vision capabilities also make it possible to monitor nocturnal animals. This can be useful for tracking migration patterns, studying animal behavior, or even for conservation purposes.

3) Agriculture technology

The Edge AI camera can monitor crops and livestock in agriculture technology. Deep-in data analysis can detect potential issues such as pests or diseases, allowing farmers to act quickly to prevent crop loss. In addition, the camera provides real-time visual data for robotics applications, such as autonomous tractors or drones, helping farmers to optimize their operations and increase yields.

4) Robotics

AI can also be applied in robotics applications, providing real-time visual data for autonomous robots. The camera’s low power consumption and small size make it an ideal option for robotics projects. In addition, the camera’s onboard MCU and software make it capable of real-time image analysis and decision-making, allowing robots to function with greater autonomy and efficiency.

5) Remote area monitoring

The Edge AI camera can be used in remote areas where other cameras may not be feasible due to their high power consumption or lack of connectivity. Low power consumption, WiFi, and BLE connectivity allow the camera to transmit data to a remote location for monitoring purposes. This can be useful for monitoring wildlife or environmental conditions in remote areas or critical infrastructure in hard-to-reach places.

Advantages of Edge AI Camera

Real-time image analysis and decision-making on the device are key advantages of the Edge AI camera.

Thanks to its powerful MCU and software, the camera can analyze images in real time and make decisions on the device without cloud processing or external hardware.

This allows for faster response times and greater efficiency, making the camera an ideal option for applications where real-time data analysis is critical.

The Edge AI Camera is an ideal option for applications where low-light conditions are a concern. Equipped with an IR diode for night vision and a light sensor for detecting the presence and quantity of light, the camera can capture data even in environments with little to no light.

Conclusion

The Edge AI Camera, developed by Maxlab, is a versatile, battery-powered camera designed for software enthusiasts without much hardware expertise with a rich set of edge AI features and applications.

Suitable for various applications, the camera features modes that enable it to function in harsh conditions and distant locations.

Maxlab is developing a full HD camera based on RISC-V architecture as the need for more capable machine vision increases.

RISC-V is open-source and more straightforward architecture than ARM. In addition, a simplified instruction set increases performance and increases battery life. Stay tuned to see future updates from Maxlab.

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