An overdose of opioids can cause the user to stop breathing, resulting in death. A physiological monitoring system monitors respiration based on oxygen saturation readings from a fingertip pulse oximeter in communication with a smart mobile device and sends opioid monitoring information from the smart mobile device to an opioid overdose monitoring service. The opioid overdose monitoring service notifies a first set of contacts when the opioid monitoring information indicates a non-distress stats and notifies a second set of contact when the opioid monitoring information indicates an overdose event. The notification can be a phone call or text message to a specified person, emergency personnel, or first responders, and can include the location of the smart mobile device. The smart mobile device can also include the location of the nearest treatment center having emergency medication used in treating opioid overdose, such as naloxone.

A medical monitoring system for use in residential facilities, nursing homes, or home environments is disclosed. The system utilizes a variety of modules and wearable medical devices that convey vital patient information to a series of smart hubs which are connected to the cloud. In the event a change in medical status of a patient occurs, the health care workers receive an Alert notifying them of which specific patient needs attention. The system is monitored using a specialized dashboard.

An arrangement is provided for monitoring the plantar temperature of the foot having a platform with at least two multi-layer temperature sensitive pads that measure the temperature of a sole of a user's feet. The platform has a scanner for scanning the bottom of the user's feet that produces a digital image thereof. A printed circuit board supports remote connectivity to a mobile application that transmits the scanned digital image of the users' feet to the mobile application for storage and delivery to a physician. The arrangement includes the mobile application that provides a series of diagnostic questions and prompts to the user and is configured to transmit data including the scanned images of the user's feet to a physician.

A system for monitoring and analyzing impact data to determine consciousness level and injuries, comprising: impact event monitoring device monitors impact event that occurs to first end-user, impact event monitoring device integrated into objects; impact event monitoring device collects impact data of objects, first end-user using sensors, impact sensing unit, motion detection unit, GPS module, image capturing unit; network module send impact data to impact event monitoring and analyzing module, impact event monitoring and analyzing module convert impact data into Yaw, Pitch and Roll data, impact event monitoring and analyzing module analyze Yaw, Pitch and Roll data with machine learning techniques and deep learning techniques; impact event monitoring and analyzing module report and send emergency notifications to second computing device, impact data accessing module enable second end-user to examine location and intensity of impact event to understand consciousness level and injuries for providing better treatment to first end-user.

An electronic sensing and allocation system is provided for a distributed water infrastructure containing a plurality of differing appliances. The system may receive, from at least one sensor upstream of the plurality of differing appliances, a plurality of signals indicative of water usage within the distributed water infrastructure. The system may output a first indication of a first volume of water together with an indicator attributing the first volume of water to a first rate schedule, and output a second indication of a second volume of water together with an indicator attributing the second volume of water to a second rate schedule. The system may enable billing of the first and second volumes of water to a consumer at differing rates based on differing uses.

Aspects of the subject disclosure may include, for example, monitoring a communication session in which a user participates, the user being at a location; obtaining sensor information indicative of a physical environment in a vicinity of the location; determining, based at least in part upon the sensor information, whether a person other than the user is in the physical environment, resulting in a determination; and responsive to the determination being that the person is in the physical environment: categorizing, based at least in part upon the sensor information, the person into one class of a plurality of classes of people; generating an alert, the alert indicating to which class the person has been categorized; and providing the alert via the communication session to a communication device being used by the user. Other embodiments are disclosed.

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. Various embodiments may determine if the patient consumed a medication dose based on machine vision, audio, or other sensor data, permitting caregiver notification of patient medication adherence, medication compliance, or non-adherence and sensor inputs as data on potential effectiveness and/or side effects.

A system for detecting an anomalous event in a person includes a body in contact with a skin surface of a person; a heat source for heating the skin surface to a target temperature; a skin temperature sensor for measuring a temperature of the skin surface in contact with the heat source; a blood volume sensor for measuring a blood volume of the skin surface; and a hardware processor communicatively coupled to the heat source, the blood volume sensor, the skin temperature sensor, and an environmental temperature sensor. The hardware processor is configured to receive a baseline blood volume signal, output a heating signal to the heat source to initiate a heating cycle, receive a second blood volume signal from the blood volume sensor, compare the second blood volume signal to the baseline blood volume signal, and determine whether an anomalous biologic event has occurred.

A method for facilitating a health protection protocol is presented. The present invention provides the storage device, the processing device, the health tracking device, and the at least one user interface device, where the health tracking device contains at least one sensor, at least one user biological data is received through the at least one sensor. At least one user biological data is transmitted from the health tracking device to the at least one user interface device. The at least one user biological data is transmitted from the at least one user interface device to the storage device. The plurality of health data is updated with the at least one user biological data through the processing device. The plurality of health data is transferred to the at least one user interface device. An at least one health statistic is generated from the plurality of health data through the processing device.

Embodiments of the present disclosure provide systems and methods for performing stroke detection with machine learning (ML) systems. The method performed by a computer system includes accessing a video of a user. The method includes performing a first test on the accessed video for detecting a facial drooping factor and speech slur factor of the user in real-time. The facial drooping factor is detected with facilitation of one or more techniques. The speech slur factor is detected with execution of machine learning algorithms. The method includes performing a second test on the user for detecting a numbness factor in hands of the user. The method includes processing the facial drooping factor, the speech slur factor, and the numbness factor for detecting symptoms of stroke in the user in real-time. The method includes sending notification to at least one emergency contact of the user in real-time for providing medical assistance.