Project Hub /Artificial Intelligence & Edge ML/Edge AI & TinyML/Time Lapse Timed Photography On MaixCam Board

Intermediate

MAIXDUINO

Project Specific

3 – 6 Hours

Complete Kit

Time Lapse Timed Photography On MaixCam Board

A Python-controlled time-lapse photography system built on the MaixCam RISC-V AI camera board for autonomous, long-duration image capture.

Originally published on ElectronicsForU

View original tutorial

Parts You'll Need

This project is sourced from another site, not written by us — this list is our best match of their components against what we stock, not a verified bill of materials. Always check the original blog (linked above) for the actual parts list before buying.

ESP32 CAM WiFi Module Bluetooth with OV2640 Camera Rs. 1,483.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

Selected: Rs. 0.00

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How It Works

The Time Lapse Timed Photography system operates autonomously on the MaixCam RISC-V AI camera board, utilizing its integrated high-performance vision sensor and built-in TFT touch screen. At the core of the system is a Python script executed via the MaixPy environment running on the board's embedded Linux OS. When initialized, the script acts as an automated intervalometer. It interfaces directly with the onboard camera module to capture high-resolution still frames at user-defined time intervals. These captured images are written sequentially to local storage, creating a chronological image set ready for compilation into a video file. Because the MaixCam features an integrated TFT touch screen, users can interact with the system locally to configure parameters, launch the script, and monitor capture status without needing an external host computer. By running the script natively on the edge AI hardware, the system eliminates the dependency on a tethered PC, ensuring reliable, continuous, long-duration operation for extended field deployments.

Why Build This

Capture multi-day or multi-week botanical transformations like plant growth and flowering cycles with precise interval timing.

Document long-term engineering milestones such as building construction or structural fabrication progress.

Record atmospheric dynamics, cloud formations, and changing weather conditions over extended periods using an autonomous edge device.

Real-World Application

Plant growth monitoring, construction site progress tracking, and recording landscape or weather changes.

Skills You'll Learn

Python programming

embedded Linux operation

intervalometer logic design

edge camera control

local storage management

GUI touch menu navigation

Safety Precautions

Run the script directly from the MaixCam TFT screen menu or autostart menu rather than via SSH or MaixVision to prevent unexpected termination if the connected computer enters sleep mode.

Technology Tags

RISC-V

AI CAMERA

PYTHON

LINUX

TIME-LAPSE PHOTOGRAPHY

TFT SCREEN

AUTOMATION

Frequently Asked Questions

Why should I run the script directly from the MaixCam TFT screen instead of via SSH?

Running the script locally via the onboard screen prevents unexpected script termination caused by network drops or if the connected host computer enters sleep mode during a long-duration capture.

Do I need an external computer to operate this time-lapse system?

No. Once the Python script is loaded onto the MaixCam board, it can be launched independently using the built-in TFT touch screen and menus.

What programming language is used to control the image capture timing?

The system is controlled using Python through the MaixPy framework running on the MaixCam board's Linux operating system.

Gallery

This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.

Kitkraft Project Hub — curated from the maker community, credited at the source.

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