Aggression detection systems typically employ artificial intelligence, machine learning, and audio/video analysis to identify and alert authorities to potentially aggressive behaviour in real-time. These systems might use various sensors, such as cameras, microphones, or other monitoring devices, to capture audio and video data in specific areas of the school environment. The gathered data is then analysed using algorithms designed to recognise patterns of aggressive behaviour, such as shouting, physical altercations, or other threatening actions like active shootings (Gillum & Kao, 2019).
Concerns raised by this type of model are multifaceted and depend on the technology used to monitor students, be it emotional facial recognition, auditory sensors, or social media monitoring. However, a common thread among these concerns is that the technologies are not entirely reliable and encroach upon students’ privacy.
