Smart Security Sensing for Predictive Deterrence Automation
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Solution Overview
Problem
Conventional security and automation systems require unnecessary intervention from users and are inefficient in monitoring and responding to events, leading to potential security breaches and property damage.
Innovation Solution
A smart sensing system that uses a control panel to monitor and predict changes in conditions within a smart environment, applying machine learning techniques to autonomously handle resources and deter potential security threats by analyzing sensor data and performing actions such as emitting sounds or sending drones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional sensing techniques are used to monitor conditions, then personnel can be informed of sensed conditions, but the system requires unnecessary intervention by personnel and is inefficient
Solution Approach 1:
The system enables resources to serve themselves through autonomous actions. The control panel automatically performs functions such as ordering resources, scheduling services, or triggering alerts without requiring personnel intervention. This self-service capability resolves the contradiction by maintaining reliable monitoring while eliminating the need for manual intervention.
Solution Approach 2:
The system performs predictions and takes preliminary actions before conditions deteriorate or events occur. By analyzing sensor data and predicting future states, the system proactively orders resources or schedules services in advance, preventing the need for reactive personnel intervention and improving operational efficiency.
2Loss of information
If conventional sensing techniques are used to report events, then occurrences can be reported, but users may still experience theft or property damage
Solution Approach 1:
The system applies preliminary anti-action by predicting potential security threats and performing deterrent actions before theft or property damage occurs. The control panel analyzes sensor data to identify suspicious patterns and triggers preventive measures such as sending alerts to authorities or activating security protocols, thereby countering harmful factors before they materialize.
Solution Approach 2:
The system implements continuous feedback loops where sensor data is constantly monitored, analyzed, and used to adjust system responses. This real-time feedback mechanism enables the system to detect anomalies, predict threats, and automatically respond with appropriate actions, transforming passive event reporting into active threat prevention.
3Productivity
If the control panel autonomously performs functions to handle resources, then system efficiency improves, but power consumption and CPU usage increase
Solution Approach 1:
The control panel employs periodic action by scheduling resource-intensive prediction and analysis operations at optimal intervals rather than continuously. The system monitors sensor data periodically and performs autonomous functions only when conditions warrant intervention, thereby maintaining high productivity while significantly reducing average power consumption and CPU usage compared to continuous operation.
Data Source
AI summary
Methods, systems, and devices for deterrence techniques using a security and automation system are described. In one method, the system may receive a set of inputs from one or more sensors of the security and automation system. The system may determine one or more characteristics of a person proximate the security and automation system based at least in part on the received set of inputs. The system may predict an event based at least in part on a correlation between the one or more characteristics and the event. The system may perform one or more security and automation actions prior to the predicted event.