Hyper Object Detection
Anticipate risks, recognise opportunities: predictive identification and intelligent responses
Analyses input frames and returns analyses for predicting horizontal interventions
Value proposition
The identification and detection of objects in real time from still or moving images.
Benefit
Reduced maintenance costs, optimised resource management, improved operational functions.
Decision Support System
What
- Artificial Intelligence solution available both on-prem and in the cloud;
- Centralised stand-alone and distributed agent platform for remote detectors and actuators.
How
Generation of ad-hoc models on real-time data.
Model Generation
How
- Loading of the initial dataset using normalised logs and verification of the generated model;
- Preparation of the API through gateway configuration.
What
- Generation of the model to be used for classification;
- Consumption of post-processed data for real-time prediction.
Image analysis
Solution
Hyper Object Detection enables predictive maintenance actions to proactively identify damage and runtimes by analysing still or moving images, either through proprietary coding or open source libraries, and integrating both video and mechanical IoT systems, even technologically outdated ones.
Hyper Object Detection
Hyper Object Detection operates in the field of image recognition. It identifies and detects objects in real time from still or moving images; it analyses input frames and returns analysis useful for the prediction of horizontal operations.
Identified Use Cases
Predictive maintenance of motorway sections
The deterioration of the road surface is the main cause of motorway accidents, a serious and widespread problem. More than half of these are caused by potholes, asphalt with micro-fractures and damaged joints, while the rest are caused by problems with signposts, safety barriers and rerouting, requiring urgent action.
Automated video surveillance system
Many realities require an advanced surveillance system, but traditional methods are ineffective for covering large areas and can generate false alarms, increasing operational costs and the risk of missed detection
of real threats.
Diagnosis of lung infections
Lung infections require rapid diagnosis. Our model, trained on thousands of images, accurately recognises conditions such as viral and bacterial pneumonias to an accuracy of more than 98%, offering concrete support to physicians in developing diagnoses and treatment plans.
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