> For the complete documentation index, see [llms.txt](https://docs.didge.io/home/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.didge.io/home/thermal-imagery-ai/end-user/core-functions/thermal-image-+-ai-+-didge.md). # Thermal Image + Ai + Didge Purpose: For Surface Temperature Monitoring and Automated AI Submission ***
### Step-by-Step Instructions #### 1. Launching the Thermal Camera * Locate the FLIR app on the home screen of the device. * Tap the app to launch the thermal camera interface.
#### 2. Understanding the Viewfinder * Once open, the camera viewfinder will show either: * A circular “Region of Interest” (ROI) with an average temperature reading, or * A pinpoint marker showing a specific temperature. * Ensure the food surface is the focus of this region for accurate readings. #### 3. Capturing the Image * Position the camera approximately 30 to 40 cm from the food item. * Allow the camera to stabilize for a few seconds. * Press the capture button to take the image. Each image will automatically generate a submission record. ***
### Temperature Guidelines | Food Type | Target Temperature Range | | ------------------ | ------------------------ | | Hot food (general) | Above 60°C | | Cooked wet dishes | Above 75°C | | Chilled foods | Below 5°C | * Always point the camera at the actual surface of the food. * Avoid capturing surrounding surfaces that could produce inaccurate temperature data.
The ai extracts that the food is an apple and at 4.7ºCflir_20250421T155009.jpg
The ai extracts the food is vegetable juice at 3.7ºCflir_20250421T154933.jpg
the ai extracts the food is kalamata olives at 4.4ºCflir_20250421T155020.jpg
The ai extracts that the food is wagyu tenderloin at 4.2ºCApril 16, 2025 at 1119AM.jpeg
the ai extracts the food is chicken at 2.5ºCApril 16, 2025 at 1208PM.jpeg
The ai cannot extract this food item, and is at 2.4ºCApril 17, 2025 at 1119AM.jpeg
*** ### Image Settings * In the FLIR app, disable any thermal overlays or color filter modes. * Only natural, visible-light images should be used. * This ensures the AI system can recognize food types, read text, and interpret labels. * Natural images lead to more reliable and accurate AI extractions. *** ### AI Automation After capturing an image: 1. It is uploaded automatically. 2. ChatGPT-4 processes the image to extract: * Food name and category * Surface temperature * Labels (e.g. supplier, expiry dates, invoice number) 3. A complete digital record is created automatically: * Includes original image, structured data, and temperature log. * Assigned to the correct area/device ID (e.g. Kitchen, Floor 3). *** ### Submissions and Reporting * Each image equals one record. * No manual login is required. * Submissions are saved and structured with: * Natural image * Extracted data * Web report (viewable online) * Downloadable formats (PDF or Excel) * View summaries and analytics via the reporting dashboard.

Incoming Goods - Record of delivery using thermal image + ai

Reheating record using thermal image + ai

*** ### Use Cases Buffet Monitoring * For surface temperature tracking during production or service. Food on display * Cold food on display * Hot food on display Incoming Goods * Capture images of incoming food and associated packaging or labels. * AI can extract supplier, product, expiry date, and other compliance fields. *** ### Tips for Best Results * Ensure the camera lens is clean. * Maintain a consistent distance of 30–40 cm from the food. * Hold the camera steady and give it time to stabilize before capturing. * Make sure the correct item is centered in the Region of Interest.

pdf export

Excel export

***
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