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Artificial intelligence (AI)

Fore-Site: Computer Vision for Field Operations

Fore-Site

Week 4 of the High Digital AI Initiatives Series. This week, we’re moving from the database to the field, exploring applied computer vision

Quick Answer: What is the Fore-Site App?

Fore-Site is a Progressive Web Application (PWA) developed by High Digital that leverages computer vision to automate field reporting. It processes uploaded images and videos to auto-fill complex compliance forms, adjusting its output based on the specific context of the report (e.g., Hazard vs. Inspection).

Eliminating the Manual Data Bottleneck

In sectors requiring rigorous compliance, manual data entry on mobile devices is prone to human error and massive time delays. Typing out granular details of site damage or routine inspections limits operational efficiency. Fore-Site solves this by shifting the burden from manual text entry to visual AI processing.

The Technical Workflow of Fore-Site

Step

Technical Process

Result

1. Image Ingestion

The PWA captures or uploads high-resolution image data from the field worker’s device.

Seamless cross-platform operability (web and mobile).

2. Object & Scene Detection

Computer vision models scan the image matrix to classify objects, assess damage, and identify environmental factors.

Raw visual data is translated into structured metadata.

3. Context-Aware Routing

The AI assesses the specific category the user has selected (Incident, Observation, Inspection, Hazard).

The model applies different validation logic depending on the report type.

4. JSON to Form Mapping

The AI generates a descriptive text narrative and maps the extracted data directly to the corresponding form fields.

A multi-minute reporting task is completed accurately in seconds.

The scope for the next phases is broad. We are exploring how we integrate with existing image capture (CCTV, Thermal, LiDAR etc)

Next Week in the AI Series: We look at the NLP architecture transforming static B2B white-papers into interactive chat experiences.

We love researching complex AI projects and data products. If you have one drop us a line

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