# Anomaly detection Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/anomaly-detection
> Markdown URL: https://aitinkerers.org/technologies/anomaly-detection.md
> Technology record last updated: 2026-04-10T22:47:21Z
> Generated: 2026-09-23T05:43:57Z

Anomaly Detection (Outlier Analysis) is the ML-driven process of flagging rare data points or events that significantly deviate from an established normal pattern.

Anomaly Detection identifies critical incidents by modeling a system's 'normal' behavior, then using statistical methods or Machine Learning (ML) to flag significant deviations as outliers. This is a vital, proactive capability across multiple sectors. For example, financial institutions use it for real-time credit card fraud detection, flagging transactions (e.g., a $5,000 purchase in a new country) that violate a user's spending baseline. In IT Operations, it monitors infrastructure metrics (CPU, latency) to predict equipment failure or system health issues before a total outage. The goal is simple: reduce false positives while ensuring early detection of high-impact events like a network intrusion or a manufacturing defect.

- Official technology site: https://www.ibm.com/topics/anomaly-detection
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Leveraging AI for Structural Safety in Mining Operations](https://bogota.aitinkerers.org/talks/rsvp_xwxTWYagvts)

The project "Anomalies Detection in Tunnels" focuses on detecting deformations and anomalies in mining tunnels to prevent structural collapses. It employs anomaly detection models applied to point clouds to analyze three-dimensional data captured during mining operations. The primary goal is to identify and assess deformations or irregularities in tunnel structures that could jeopardize the safety and stability of excavation operations. By utilizing advanced data analysis techniques and machine learning models, the project aims to provide accurate tools for monitoring and early intervention, thus preventing potential collapses and ensuring the integrity of mining operations.

- Event context: AI Tinkerers Bogotá No. 4 — 2024-08-29 — Bogotá
- Public talk page: https://bogota.aitinkerers.org/talks/rsvp_xwxTWYagvts

### [Zoobot: a Foundation Model for Galaxies](https://toronto.aitinkerers.org/talks/rsvp_eX-ZjRbJY7U)

Modern telescopes take far more images than astronomers could ever look through. Zoobot is a foundation model for automatically answering questions about galaxy images (like - does this galaxy have spiral arms?). By training on over 100M crowdsourced annotations from volunteers, Zoobot learns a semantic representation of each image that is useful for similarity search, anomaly detection, personalized recommendation, and (of course) efficient finetuning to new science questions.

- Event context: AI Tinkerers Toronto - Inaugural Meetup — 2024-04-11 — Toronto
- Public talk page: https://toronto.aitinkerers.org/talks/rsvp_eX-ZjRbJY7U

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