Tyco Fire & Security GmbH (20240331071). MACHINE LEARNING SYSTEMS AND METHODS FOR BUILDING SECURITY RECOMMENDATION GENERATION simplified abstract
Contents
MACHINE LEARNING SYSTEMS AND METHODS FOR BUILDING SECURITY RECOMMENDATION GENERATION
Organization Name
Inventor(s)
Jason M. Ouellette of Sterling MA (US)
Saravanabavanandam Sadaksharam of Plano TX (US)
Gopal Paripally of North Andover MA (US)
Glenn Holton of Braintree MA (US)
Yohai Falik of Petah Tivka (IL)
MACHINE LEARNING SYSTEMS AND METHODS FOR BUILDING SECURITY RECOMMENDATION GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240331071 titled 'MACHINE LEARNING SYSTEMS AND METHODS FOR BUILDING SECURITY RECOMMENDATION GENERATION
Simplified Explanation: The patent application relates to generating autonomous building security recommendations using sensor data and machine learning models.
- **Key Features and Innovation:**
- Utilizes sensor data from building systems for security recommendations. - Machine learning model trained with data from various sources. - Presents notifications for recommended actions to operators.
- **Potential Applications:**
- Enhancing building security systems. - Improving response time to security threats. - Streamlining security operations in large buildings.
- **Problems Solved:**
- Providing real-time security recommendations. - Integrating sensor data for actionable insights. - Enhancing overall building security protocols.
- **Benefits:**
- Increased efficiency in security operations. - Improved response to security incidents. - Enhanced overall building safety.
- **Commercial Applications:**
- "Autonomous Building Security Recommendation Generation" technology can be utilized by security companies, building management firms, and smart building developers to enhance security measures and response protocols in various commercial and residential buildings.
- **Prior Art:**
- Further research can be conducted in the field of autonomous building security systems and machine learning applications in security operations.
- **Frequently Updated Research:**
- Stay updated on advancements in machine learning models for building security applications.
Questions about Autonomous Building Security Recommendation Generation:
1. *How does the use of sensor data improve building security recommendations?*
- Sensor data provides real-time insights into building conditions, enabling more accurate and timely security recommendations based on the current environment.
2. *What are the potential implications of autonomous security recommendation generation in the building management industry?*
- The technology can revolutionize security operations by automating and optimizing response protocols, leading to enhanced safety and efficiency in building security management.
Original Abstract Submitted
systems and methods are disclosed relating to autonomous building security recommendation generation. for example, a method can include receiving, by one or more processors, sensor data from one or more sensors associated with a building system. the method can further include determining, by the one or more processors using a machine learning model and the sensor data, a recommended action for an operator to perform, the machine learning model trained using training data comprising data retrieved from one or more data sources maintained by at least one of a first entity associated with the building system or a second entity associated with the one or more sensors. the method can further include presenting, by the one or more processors using at least one of a display device or an audio output device, a notification corresponding to the recommended action.
