Abstract: Apparatus and associated software and methods for improving medication adherence. A connected medication dispenser includes a robotic arm adapted to deliver a prescribed medication dose to a patient in their home, and software and sensors that analyze the patient's compliance, communicate with external health sensors to monitor the patient's response to the dose, and communicate with external servers to send the result of providing the medication dose to the patient. In an illustrative example, the patient may be a chronic, acute, or terminal illness patient, and the results may be communicated with physicians, payers, caregivers, a pharmacy, and/or the patient's electronic health record. The flow of information may allow the physician or caregiver to offer real-time adjustments to the medication type, dose, and schedule to provide improved therapeutic outcomes.

Abstract: Apparatus and associated methods relate to a connected pill dispenser configured to treat a patient's illness with a robotic arm adapted to deliver a prescribed medication dose to a patient in their home, analyze the patient's response to the dose based on various sensor inputs, automatically determine whether the patient took the medicine and send the provider the result of providing the medication dose to the patient. In an illustrative example, the patient may be a chronic, acute, or terminal illness patient. The medication dose may be, for example, a medication prescribed by a doctor to be taken in a specific amount at specific times. In some embodiments, the connected pill dispenser may automatically notify the patient when a medication dose is due.

Abstract: A device may determine whether a mobile device is associated with a first identifier that is associated with a first mobile network based on determining that a second identifier associated with the mobile device is associated with a second mobile network. The first identifier may provide authorization for the mobile device to a private network associated with the first mobile network. The device may transmit, based on determining that the mobile device is associated with the first identifier, a security challenge to the mobile device. The device may determine, based on receiving a response to the security challenge from the mobile device, whether the response to the security challenge satisfies the security challenge. The device may provide, based on determining that the response to the security challenge satisfies the security challenge, the mobile device with access to the private network.

Abstract: Apparatus and associated methods relate to a connected pill dispenser configured to treat a patient's illness with a robotic arm adapted to deliver a prescribed medication dose to a patient in their home, analyze the patient's response to the dose based on various sensor inputs, automatically determine whether the patient took the medicine and send the provider the result of providing the medication dose to the patient. In an illustrative example, the patient may be a chronic, acute, or terminal illness patient. The medication dose may be, for example, a medication prescribed by a doctor to be taken in a specific amount at specific times. In some embodiments, the connected pill dispenser may automatically notify the patient when a medication dose is due.

Abstract: A device may determine whether a mobile device is associated with a first identifier that is associated with a first mobile network based on determining that a second identifier associated with the mobile device is associated with a second mobile network. The first identifier may provide authorization for the mobile device to a private network associated with the first mobile network. The device may transmit, based on determining that the mobile device is associated with the first identifier, a security challenge to the mobile device. The device may determine, based on receiving a response to the security challenge from the mobile device, whether the response to the security challenge satisfies the security challenge. The device may provide, based on determining that the response to the security challenge satisfies the security challenge, the mobile device with access to the private network.

Abstract: A method includes receiving, at a fraud management device, at least one BSID associated with communication data from at least one MTC device. The fraud management device determines a location associated with the at least one BSID. Relevant data elements are selected from the communication data. The fraud management device applies known domain rules to the communication data and identifies a connectivity pattern for the at least one MTC device based on the communication data. An anomaly detection model is applied to particular communication data associated with a particular MTC device based on the connectivity pattern, and at least one anomaly from the identified connection pattern is detected based on the anomaly detection model.

Abstract: Exemplary subscriber identification module (“SIM”) based machine-to-machine (“M2M”) client systems, methods, and apparatuses are described herein. An exemplary M2M device includes an M2M SIM client implemented on a SIM card installed in the M2M device. The M2M SIM client provides a platform messaging interface through which the M2M device communicates with an M2M platform, provides a device-side interface through which the M2M device interfaces with the M2M SIM client, and provides a set of one or more M2M services to the M2M device. The set of M2M services may include one or more of the exemplary M2M services described herein. Corresponding systems, methods, and apparatuses are also described.

Abstract: A method includes receiving, at a fraud management device, at least one BSID associated with communication data from at least one MTC device. The fraud management device determines a location associated with the at least one BSID. Relevant data elements are selected from the communication data. The fraud management device applies known domain rules to the communication data and identifies a connectivity pattern for the at least one MTC device based on the communication data. An anomaly detection model is applied to particular communication data associated with a particular MTC device based on the connectivity pattern, and at least one anomaly from the identified connection pattern is detected based on the anomaly detection model.

Abstract: Exemplary subscriber identification module (“SIM”) based machine-to-machine (“M2M”) client systems, methods, and apparatuses are described herein. An exemplary M2M device includes an M2M SIM client implemented on a SIM card installed in the M2M device. The M2M SIM client provides a platform messaging interface through which the M2M device communicates with an M2M platform, provides a device-side interface through which the M2M device interfaces with the M2M SIM client, and provides a set of one or more M2M services to the M2M device. The set of M2M services may include one or more of the exemplary M2M services described herein. Corresponding systems, methods, and apparatuses are also described.