KeyView.ai uses AI models to recognize weather conditions by analyzing live video feeds. This includes detecting rainfall, snow accumulation, wind movement, and overcast conditions around the property. Daily logs are generated to correlate property activity with weather events, helping explain anomalies in traffic or maintenance. Notifications can be configured to alert staff during adverse weather, supporting proactive facility management. Feedback from weather inaccuracies is used to retrain the model and improve detection precision.

The system detects when a garbage truck enters the premises, confirms pickup completion, and logs the time of service. Reports can be automatically shared with property managers or vendors to ensure service-level agreements are met. If a scheduled pickup does not occur, an alert is sent to the manager with video evidence. A feedback loop allows managers to flag missed detections, helping the system better identify various truck types or service styles. This enhances vendor accountability and property cleanliness.

AI models monitor for violent or aggressive behavior using pose and motion analysis. If suspicious behavior is identified (e.g., a physical altercation or sudden aggressive movement), the system sends real-time alerts with video clips to the property manager or security team. Incidents are logged and available in the activity report dashboard for further review. Continuous feedback from confirmed or false-positive events is used to refine the behavior detection algorithm. This service enhances safety for tenants and visitors.

KeyView.ai detects landscaping equipment and personnel through motion recognition and object classification. The platform logs when lawn care begins and ends, creating automated service reports with timestamps and visuals. If expected services are not detected within a maintenance window, a notification is sent to management. Property managers can flag errors or confirm completed services to train the system more accurately over time. This ensures vendor compliance and grounds are maintained regularly.

Using video feeds from entry and exit points, KeyView.ai counts vehicles and analyzes peak usage hours. The system creates daily and weekly traffic reports that help property owners understand flow trends and plan logistics. Alerts can be triggered for unusual spikes, such as unexpected large gatherings or blocked entrances. Reports are exportable for insurance, leasing, or planning purposes. Continuous refinement occurs based on vehicle classification and feedback from edge cases (e.g., delivery trucks vs. personal vehicles).

Using movement patterns and body positioning, the system identifies falls and triggers immediate alerts to designated responders. Incidents are logged with time, location, and visual context to aid follow-up. Daily reports include any detected fall events for auditing and safety review. Managers can verify real or false detections to enhance model reliability. This reduces liability risks and speeds up response times to potentially serious incidents.

KeyView.ai identifies emergency vehicles by detecting flashing lights, vehicle profiles, and movement patterns. When such a vehicle is detected on or near the property, real-time alerts are sent to designated personnel for immediate situational awareness. Logged appearances of emergency vehicles can help validate response times or trigger internal incident reviews. Reports can be filtered by type (police, fire, ambulance) and time of day. False positives can be flagged to refine vehicle recognition models.

The platform monitors lighting across the property at night, identifying dim, flickering, or non-functional bulbs. Detected issues are logged in the maintenance dashboard with timestamps and affected zones. A notification is sent to facility teams, reducing downtime and improving safety. Weekly reports can be reviewed to track lighting reliability and schedule preventive maintenance. Feedback from manual bulb replacements helps update detection accuracy over time.

The system compares property access timestamps against business hours to identify unauthorized presence. Detected trespassing events are immediately flagged, with alerts sent to security or property managers including time-stamped video evidence. Reports highlight frequency, entry points, and duration of trespasses to aid in enforcement or deterrence. Property teams can confirm valid or invalid detections to train the system to ignore known staff or authorized activity. This service is critical for liability management and after-hours property security.