4G Connectivity · Custom Development for Enterprises

4G Edge AI Vision Terminal Development

For visual product companies, industry equipment manufacturers and algorithm integration teams, integrate specified algorithms, cameras and 4G links, and develop event structuring, image or video clip upload, log and model version management.

Video images and edge vision terminalsSoftware, hardware and system integration testingPhased delivery

SERVICE OVERVIEW

Service overview

4G Edge AI vision terminal development is aimed at enterprise projects that "complete identification on site first, and then upload events and evidence." Winge Technology carries out the docking of terminal hardware, embedded software and business systems based on existing equipment and target functions, forming design data and programs that can be used for subsequent integration testing, deployment and maintenance.

  • Device and interface access
  • Product business functions
  • Platform and data connection
  • Exception handling and operational constraints

DEVELOPMENT SCOPE

Development services

Development Scope

01

Device and interface access

Integrate the specified camera, main controller, algorithm running environment and 4G module, configure model input, event fields and image evidence storage strategy.

02

Product business functions

Integrate specified algorithms, cameras and 4G links to develop event structuring, image or video clip upload, log and model version management.

03

Platform and data connection

Combined with the business link of image collection → encoding or local inference → video recording and evidence caching → 4G → video or event platform, the device identity, data fields, update time, abnormal status and result confirmation method are defined.

04

Exception handling and operational constraints

The algorithm effect is determined by target samples and field testing; 4G development covers networking and data links, and model training and recognition tasks are separately defined.

Data and Operational Workflow

Image collection → Local algorithm reasoning → Event and evidence generation → 4G upload → Platform review, retrieval and equipment operation and maintenance.

The device side, communication side and platform side retain necessary status and logs respectively. Project integration testing is checked with actual equipment data and execution results, and network connection status and business completion status are recorded separately.

Project Inputs

  • Existing device models, interface and wiring diagrams, licensing agreements, data samples and available codes.
  • Business processes and parameters: target algorithm, image input, event frequency, evidence cache and model version.
  • Target location, operator, SIM/APN, power supply, installation method and equipment size.
  • Existing platform interfaces, user roles, development modules, number of prototypes and planned nodes.

Deliverables and Acceptance

DeliverablesDelivery contentVerification method
product realizationHardware design data, prototypes or existing equipment modification data involved in the project, as well as corresponding firmware and interfacesCheck event fields with corresponding images or clips.
Business integration testingData fields, status definitions, platform adaptation procedures and business integration testing recordsTest evidence caching during network outages.
Version and test dataTarget hardware and software versions, build or deployment instructions, parameter configurations and test logsRecord the target model, input conditions, processing speed and resource usage.

First confirm the scope and key functions, then complete prototype or software development, system integration testing and stage acceptance. The acceptance conditions list the prototype, version, environment, duration and passing threshold; source code, design documents, third-party licenses, materials, traffic, cloud resources and on-site work are agreed separately.

Frequently Asked Questions

Can I only upload the recognition event without continuously uploading the video?

Events, pictures or short clips can be uploaded after inference is completed on the device. It is necessary to determine the evidence retention, triggering frequency and caching rules, and verify the resource and traffic conditions when abnormalities occur frequently.

Is it possible to delegate only part of the functionality of an edge AI vision terminal?

The device interface, terminal program, 4G communication and platform integration testing can be split based on the existing R&D foundation. Please provide existing information and target boundaries, first check the "target algorithm, image input, event frequency, evidence cache and model version", and then clarify the deliverables and interface responsibilities of each module.

How are costs and cycle time assessed?

Split the workload based on target devices, interfaces, existing data, and verification criteria. This project focuses on checking the target algorithm, image input, event frequency, evidence cache and model version; when prototypes, on-site integration testing or third-party platform cooperation are required, the corresponding costs, prerequisites and nodes will be listed separately.

PROJECT DELIVERY

From requirements to delivery

01

Requirements review

Confirm business goals, existing devices and systems, interfaces and deployment conditions.

02

Scope and solution

Review technical dependencies and agree responsibilities, deliverables and acceptance methods.

03

Development and integration

Implement the agreed scope and integrate with the target devices and systems.

04

Testing and issue resolution

Run agreed test cases and record issues, fixes and regression results.

05

Handover and acceptance

Deliver the agreed work, build configurations, interface documentation and test records.

06

Maintenance and changes

Handle version maintenance and assess new requirements within the agreed support scope.

Define Devices, Interfaces and Deliverables

Please provide the target functions, existing equipment information and usage environment of the 4G edge AI vision terminal, focusing on the target algorithm, image input, event frequency, evidence cache and model version, so as to facilitate the determination of technical scope and stage delivery arrangements.

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