DAQ-IOT Wireless Time-lapse Camera Photo Capture Video Surveillance WiFi/4G/Network Port Take Photos Regularly SD Card Storage Wireless FTP Server

七月 20, 2023

1. Product Overview

4G version time-lapse camera

DAQ-GP-CAM is a wireless time-lapse camera based on 4G or WiFi, which can take pictures at certain intervals and upload to FTP server, launched by Shanghai Data Acquisition IOT Technology Co., Ltd. It can be widely used to capture the data of instruments, and can also be used for photo capture and video surveillance in the fields of cultural relics, rock and soil, hydrology and water conservancy.

This product supports WiFi/4G Ethernet access to the network, take photos regularly and upload the photos to the designated FTP server or store them in an SD card. With 4G wireless network card, it can be used in scenarios where there is no WiFi network outdoors.

2 Service Concept

Our company solemnly promise you:

You buy more than just products, but also meticulous and thoughtful technical support.

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

Free IOT solution consulting services!

3 Product Characteristic Parameters

3.1 Camera Parameters and Selection

Pixels: 2 million, 3 million, 5 million optional, default 2 million

Lens: 2.8mm/4mm/6mm

Lens specifications	2.8mm	4mm	6mm
Monitoring angle	90 degrees	80 degrees	70 degrees
Monitor distance	0~5m	0~10m	6~20m

SD card：Yes

Power supply: 12V DC

Weight: 0.35kg

3.2 Electrical Characteristics

Power supply mode: 12V DC or battery power

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

3.3 Communication Characteristics

Default networking mode: Ethernet/WiFi, 4G

Image upload: FTP server

3.4 Structural Characteristics

Antenna type: glue stick type external antenna

Material: PC plastic (shell)

Main body protection level: IP65

Size: 50mm×50mm×30mm

3.5 Working Environment

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

4 Component Matching

Equipped with 12V lithium battery pack

Time control switch (cut off the power when idle, save power)

Camera bottom mounting bracket

5 The Core Advantages of the Product

u Simple installation and rapid deployment, helping IoT projects to land quickly

u Small size

u Rainproof, suitable for outdoor environments

u Comes with fill light, suitable for taking photos at night

u Remote configuration of parameters

6 WiFi Camera Configuration

6.1 Connect to Computer

Power on the camera and connect it to the computer with a network cable.

Check the IP address on the camera label, the default is 192.168.1.88 (the actual value on the camera label shall prevail).

Set the computer IP to the same network segment as the camera, enter the camera IP in the browser, and enter the login interface

By default, the username and password are admin (actually subject to the camera label).

6.2 WiFi Settings

7 Timed Photo Upload Settings

Capture photos can be stored to SD card or uploaded to FTP server at any time and interval.

Time-lapse interval setting

FTP parameter settings

Example image upload result

8 Custom Development of Dashboard Recognition Software

8.1 Introduction to Pointer Meter Recognition/OCR Algorithms

Gaussian Filtering is generally used for image noise reduction. Canny Edge Detection method is generally used for edge detection of preprocessed images. Find the profile of the meter and panel by accurately filtering various non-critical targets. The instrument scale and instrument pointer can be detected by Hough transform, and the liquid level can also be detected by Hough transform. For the targets that need to do image classification, deep learning methods are adopted, such as number recognition, instrument style recognition and text position detection in natural scenes. The model adopts the convolutional neural network (CNN) model of deep learning, and builds different network models according to the features of the images.

Pointer type instrument recognition is mainly for pointer type instrument, which is a function of automatic recognition of industrial instrument recognition through video images.

The identification process is: using some special methods to complete the effective area screening and the pointer positioning of the instrument, according to the dial center to the dial center of the line and the Angle of the sub-dial 0 scale line, calculate the Angle between the sub-dial 0 scale line and the pointer pointing line segment, and further identify and interpret the pointer reading. The experimental results show that the algorithm is simple and accurate, and overcomes the influence of the dial's random Angle tilt on the reading recognition algorithm.