Abstract: A point of sale (POS) device includes a nest portion and a cradle portion. The nest portion includes one or more payment card or near field communication (NFC) readers. The cradle portion couples to differently-sized interchangeable frames, which in turn help secure a mobile computing device to the cradle portion of the POS device. The mobile computing device is connected via a connector to the rest of the POS device. Payment card information read by the readers is conveyed to the mobile computing device over the connector for processing. The POS device may also include tamper detection circuitry.

Abstract: A brick-and-mortar (BAM) store control system uses sensors and wireless transceivers to track customers, merchant representatives, devices, and/or objects within a BAM store area. The system can identify and track product and/or service inventory within the BAM store area and/or in individual's personal inventories, for instance by detecting movements of objects by individuals in sensor data. The system can generate inventory replenishment schedules, for instance based on inventory quantity patterns. The system can provide recommendations to customers and/or merchants, for example recommending products that customers have interacted with. The system can identify individuals and/or objects using a machine learning algorithm, which can learn based on feedback. The system can generate temporary identifiers for unrecognized individuals or objects, which it can merge or convert into long-term identifiers as more information is received.

Abstract: A point of sale (POS) device includes a nest portion and a cradle portion. The nest portion includes one or more payment card or near field communication (NFC) readers. The cradle portion couples to differently-sized interchangeable frames, which in turn help secure a mobile computing device to the cradle portion of the POS device. The mobile computing device is connected via a connector to the rest of the POS device. Payment card information read by the readers is conveyed to the mobile computing device over the connector for processing. The POS device may also include tamper detection circuitry.

Abstract: A point of sale (POS) device includes a nest portion and a cradle portion. The nest portion includes one or more payment card or near field communication (NFC) readers. The cradle portion couples to differently-sized interchangeable frames, which in turn help secure a mobile computing device to the cradle portion of the POS device. The mobile computing device is connected via a connector to the rest of the POS device. Payment card information read by the readers is conveyed to the mobile computing device over the connector for processing. The POS device may also include tamper detection circuitry.

Abstract: Point of sale (POS) systems and methods are described. A POS device includes a housing with a payment instrument reader. The payment instrument reader reads payment instrument information from a payment instrument in response to receipt of the payment instrument at a read area of the housing. The POS device includes a first fastening mechanism that secures the housing to a mount that is coupled to a surface of the environment. The POS device includes a cradle of the housing that receives a mobile computing device. The POS device includes a second fastening mechanism that secures the mobile computing device within the cradle. The POS device includes a connector coupled to the payment instrument reader and extending into the cradle. The connector is configured to couple to the mobile computing device in the cradle, to convey the payment instrument information from the payment instrument reader to the mobile computing device.

Abstract: A brick-and-mortar (BAM) store control system uses sensors and wireless transceivers to track customers, merchant representatives, devices, and/or objects within a BAM store area. The system can identify and track product and/or service inventory within the BAM store area and/or in individual's personal inventories, for instance by detecting movements of objects by individuals in sensor data. The system can generate inventory replenishment schedules, for instance based on inventory quantity patterns. The system can provide recommendations to customers and/or merchants, for example recommending products that customers have interacted with. The system can identify individuals and/or objects using a machine learning algorithm, which can learn based on feedback. The system can generate temporary identifiers for unrecognized individuals or objects, which it can merge or convert into long-term identifiers as more information is received.