Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for canine assisted home monitoring. The methods, systems, and apparatus include actions of: obtaining a reference signal from an animal at a property; determining whether an event occurred at the property corresponding to when the reference signal from the animal was received; in response to a determination that the event occurred at the property corresponding to when the reference signal from the animal was received, determining that the reference signal indicates that the event is likely occurring at the property; obtaining a sample signal from the animal at the property; determining whether the sample signal corresponds to the reference signal; and notifying a user that the event, which was determined to be indicated by the reference signal, is likely occurring again at the property.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for canine assisted home monitoring. The methods, systems, and apparatus include actions of: obtaining a reference signal from an animal at a property; determining whether an event occurred at the property corresponding to when the reference signal from the animal was received; in response to a determination that the event occurred at the property corresponding to when the reference signal from the animal was received, determining that the reference signal indicates that the event is likely occurring at the property; obtaining a sample signal from the animal at the property; determining whether the sample signal corresponds to the reference signal; and notifying a user that the event, which was determined to be indicated by the reference signal, is likely occurring again at the property.

An alarm system includes a latch assembly having a movable element mounted on one of an entry and a structural element, and a fixed element mounted on the other of the entry and the structural element, wherein the movable element is movable between an engaged position with the fixed element and a disengaged position from the fixed element. A magnet is provided in one of the movable element and the fixed element, and a coil is provided in the other of the moveable element and the fixed element. The magnet and the coil are positioned relative to each other so that an electric current is induced in the coil by the magnet when the movable element is moved between the engaged position and the disengaged position. An energy harvesting circuit connected to the coil converts the induced electric current into a supply voltage that powers the alarm system.

An alarm system includes a latch assembly having a movable element mounted on one of an entry and a structural element, and a fixed element mounted on the other of the entry and the structural element, wherein the movable element is movable between an engaged position with the fixed element and a disengaged position from the fixed element. A magnet is provided in one of the movable element and the fixed element, and a coil is provided in the other of the moveable element and the fixed element. The magnet and the coil are positioned relative to each other so that an electric current is induced in the coil by the magnet when the movable element is moved between the engaged position and the disengaged position. An energy harvesting circuit connected to the coil converts the induced electric current into a supply voltage that powers the alarm system.

A smart entry point spatial security system is intended for securing facility and other entrances in general. The system includes a device associated to an entry point. The device can be coupled externally to the entry point or natively as built-in to the entry point structure or any entry point subcomponents, such as knobs and locks. A host device with a software application monitors or observes the entry point sensor data via wired or wireless link such as Bluetooth. The sensor includes a software algorithm that is adapted to trigger safety alarms upon unauthorized usage of the entry point or as means of regulating entrance of users to a dedicated general space. The sensor data is stored locally on a host computer and a logging system is available on cloud computing device. The stored data will be used in further optimizing spatial data.

A smart entry point spatial security system is intended for securing facility and other entrances in general. The system includes a device associated to an entry point. The device can be coupled externally to the entry point or natively as built-in to the entry point structure or any entry point subcomponents, such as knobs and locks. A host device with a software application monitors or observes the entry point sensor data via wired or wireless link such as Bluetooth. The sensor includes a software algorithm that is adapted to trigger safety alarms upon unauthorized usage of the entry point or as means of regulating entrance of users to a dedicated general space. The sensor data is stored locally on a host computer and a logging system is available on cloud computing device. The stored data will be used in further optimizing spatial data.

Detecting and controlling fraud in centralized processing is provided. A system receives data packets carrying electronic transactions, and clusters the electronic transactions based on an intermediary identifier of each of the electronic transactions to identify a first cluster and a second cluster. The system generates a first model for the first cluster and a second model for the second cluster. The system detects a fraudulent electronic transaction having a first source identifier. The system locks a first data structure to prevent transfer of a first resource in electronic transactions associated with the first source identifier. The system identifies source identifiers associated with the first cluster in a first tier. The system locks absent detection of the fraudulent electronic transaction in one or more electronic transaction associated with the source identifiers, the data structure corresponding to each of the source identifiers in the first cluster.

Detecting and controlling fraud in centralized processing is provided. A system receives data packets carrying electronic transactions, and clusters the electronic transactions based on an intermediary identifier of each of the electronic transactions to identify a first cluster and a second cluster. The system generates a first model for the first cluster and a second model for the second cluster. The system detects a fraudulent electronic transaction having a first source identifier. The system locks a first data structure to prevent transfer of a first resource in electronic transactions associated with the first source identifier. The system identifies source identifiers associated with the first cluster in a first tier. The system locks absent detection of the fraudulent electronic transaction in one or more electronic transaction associated with the source identifiers, the data structure corresponding to each of the source identifiers in the first cluster.

This application describes systems and methods for locating, securing, accessing and utilizing a discrete enclosure or workspace. The discrete enclosure or workspace may be located in a public, private or semi-private setting and may comprise a combination of working platforms or surfaces, seats, desks and other apparatus, as well as computer hardware and software. Systems may comprise natural language processing, artificial intelligence, machine learning and other adaptive learning capabilities to enhance the use of the discrete workspace. The workspace may be dimensioned to be used for a wide variety of activities by one or more users.

This application describes systems and methods for locating, securing, accessing and utilizing a discrete enclosure or workspace. The discrete enclosure or workspace may be located in a public, private or semi-private setting and may comprise a combination of working platforms or surfaces, seats, desks and other apparatus, as well as computer hardware and software. Systems may comprise natural language processing, artificial intelligence, machine learning and other adaptive learning capabilities to enhance the use of the discrete workspace. The workspace may be dimensioned to be used for a wide variety of activities by one or more users.