Wireless timed camera product manual.

七月 16, 2025

1 Productoverview

4G version of the camera that takes photos at regular intervals

SC-GP-CAM01 is a camera launched by Shanghai Shucai Internet of Things Technology Co., LTD., which is based on 4G or wifi and can take photos at regular intervals, capture videos, upload photos to FTP. It can be widely used in the capture and recognition of instrument readings, photo capture and video surveillance in cultural relics, geotechnical engineering, hydrology and water conservancy fields.

This product supports wifi/4G Ethernet access to the network, and can take photos at regular intervals and upload them to the specified FTP server or store them in the SD card. With 4G wireless network card, it can be used in outdoor scenes without wifi network.

2 service idea

Our company Zhengzhou promises:

You are not only buying a product, but also meticulous and thoughtful technical support services.

We provide remote guidance, remote configuration and debugging services for free, and send data to the server specified by the customer.

Free consulting service on Internet of Things solutions!

3 Product characteristic parameters

3.1 Camera parameters and selection

Pixels: 2,000,000,3,000,000,5,000,000 are optional, default is 2,000,000

Lens: 2.8mm/4mm/6mm

Lens specification	2.8mm	4mm	6mm
The monitoring Angle	90 degrees	80 degrees	70 degrees
Keep your distance	0~5m	0~10m	6~20m

Memory card function: support

Power supply: 12V DC

Weight: 0.35kg

3.2 electrical character

Power supply: 12V DC or battery power

(Power interface: DC5.5*2.1mm Mother socket, positive inside and negative outside)

3.3 Communication characteristics

Default networking mode: Ethernet /WiFi, 4G

Image upload: FTP server

3.4 structural property

Antenna type: rubber stick external antenna

Material: PC plastic (shell)

Main protection class: IP65

Size: 50mm x 50mm x 30mm

3.5 work environment

Environmental temperature-30°C~70°C, humidity 0~95% (non-condensing)

4 Component matching

Accompanied by 12V lithium battery pack

Time control switch (cut off power supply during idle time to save energy)

The camera is mounted on a fixed bracket at the bottom

5 Core product advantages

u Simple installation and rapid deployment help the Internet of Things project to be implemented quickly

u Small size

u Rainproof design, suitable for outdoor environment

u Built-in flash, suitable for night photography

u Supports remote configuration parameters

6 WiFi camera configuration

6.1 Connect to the computer

Plug the camera in and connect it to your computer with a network cable.

Check the IP address on the camera label. The default is 192.168.1.88 (actual IP address is subject to the camera label).

Set the computer IP to be in the same subnet as the camera, enter the camera IP in the browser, and press Enter to enter the login interface

The default user name and password are both admin (the actual one is on the camera label).

6.2 WiFi set up

7 Set up to take photos at regular intervals and upload them

You can set any time and interval to capture photos and store them to SD card or upload them to FTP server.

Set the interval between photos

FTP parameter setting

Example of image upload results

8 Custom development of dashboard recognition software

8.1 Introduction to pointer instrument recognition/OCR algorithm

For the collected images, Gaussian Filtering is typically used to reduce noise. For the pre-processed images, the Canny Edge Detection method is employed for edge detection, which precisely filters out non-critical elements to identify the contours of instruments and panels. The Hough Transform is used to detect instrument scales and pointers, as well as to measure liquid levels. For image classification tasks, such as digital recognition, instrument style recognition, and text location detection in natural scenes, deep learning methods are utilized. The model employs a deep convolutional neural network (CNN) to construct different network models based on the features of the images.

Pointer instrument recognition is mainly for pointer instruments, which is automatic identification of industrial instruments through video images.

The process of identification involves using specific methods to effectively screen the area and locate the instrument's pointer. By calculating the angle between the line from the center of the dial to the pointer's rotation center and the 0-degree mark on the sub-dial, the algorithm can determine the angle between the sub-dial's 0-degree mark and the pointer's pointing line segment, thus further identifying and interpreting the pointer reading. Experimental results show that this positioning and recognition algorithm is simple to calculate, has a high accuracy rate, and overcomes the impact of random angle tilts on the dial on the reading recognition algorithm.