One of the key ways Plum helps reduce false alarms is through its sophisticated object recognition capabilities. Our AI algorithms are trained to differentiate between various objects and activities commonly found in property environments, such as humans, vehicles, animals, and environmental factors like moving vegetation or changing lighting conditions. By accurately identifying and categorizing these elements, our system minimizes false alarms triggered by non-threatening events, such as animals passing by or changes in weather.

Plum integrates advanced behavioral analysis into its AI algorithms. This means our systems not only detect motion but also analyze the behavior patterns associated with detected objects. For example, our AI can distinguish between routine activities like a delivery person approaching a building and suspicious behavior like loitering or attempted unauthorized access. By understanding the context and intent behind movements, Plum reduces false alarms caused by harmless activities, ensuring that alerts are relevant and actionable.

Our AI-powered CCTV monitoring service offers real-time video analytics capabilities. This allows our systems to continuously analyze live video feeds and provide intelligent alerts based on predefined criteria and rules. Operators receive alerts only when there is a genuine security threat or anomaly, supported by contextual information and insights provided by our AI technology. This proactive approach not only reduces false alarms but also improves response times and security incident management.

Plum captures and recognizes human faces and vehicle number plates. You can quickly check a person’s photo or a vehicle number, full or partial, against the video footage. Multiple camera search is also possible.

By continuously analysing security data and trends, we can develop comprehensive threat models that help us anticipate and prepare for a wide range of potential security challenges.