Processing n-dimensional radar data to find the unexpected within the expected has traditionally been a difficult and fuzzy process. Anomaly detection software requires the use of assumed models and numerical estimations which makes all results uncertain. Uncertain results can range from potentially close to the truth to extremely far off, with no reliable way to know how far off the results are. This makes it ineffective/unsafe for implementation into autonomous heavy equipment.
The OI Core Technology analysis takes a completely different approach. It provides the exact center point and geometry of any data set in real time. This lets radar processing flag unexpected data and its magnitude and direction from an ideal state in real time. Changes in terrain, moving objects (e.g. humans) and any other real-world situations that may arise are determined reliably and robustly to trigger corresponding alarms.
The most impactful benefit is saving of human life, as a false negative from uncertain technology could mean that heavy equipment does not consider their presence when operating. Elimination of false positives also saves unnecessary stops and downtime.
Avoiding both false positives and false negatives when it comes to terrain changes can be a game-changing ability that saves heavy equipment from being damaged or compromised.