An example patient scheduling system can include: at least one processor; and system memory encoding instructions which, when executed by the at least one processor, cause the system to: provide a schedule for a patient, the schedule defining care items associated with the patient; allow for acceptance of a patient care activity; and notify a caregiver and the patient of changes to the patient care activity.

A computerized-method for managing staffing-variances in a contact-center is provided herein. The computerized-method includes: (i) retrieving, a plurality of forecasts and corresponding schedules of working-shifts, from a database-of-a-plurality-of-agents-with-respective-plurality-of-scheduled-working-shifts; (ii) analyzing the retrieved forecasts, by monitoring net-staffing-levels to identify one or more time-intervals, in the retrieved forecasts which have the staffing-variance; (iii) using pretrained Machine Learning models to detect one or more agents that will most likely accept one or more time-intervals from the identified one or more time-intervals to store the one or more agents in the database-of-a-plurality-of-agents-with-respective-plurality-of-scheduled-working-shifts; (iv) retrieving each detected agent from the database-of-a-plurality-of-agents-with-respective-plurality-of-scheduled-working-shifts to create a working-opportunity to amend staffing-variance in one or more time-intervals; and (v) reaching out each detected agent, by broadcasting the created working-opportunity to a computerized-device of corresponding agent, to be presented via a display unit, that is associated to the computerized-device.

A method of providing artificial intelligence (AI) functionality to target legacy customer outreach platforms of a plurality of tenant enterprises includes storing a plurality of AI templates, each of which is associated with one or more AI routines, generating a campaign object associating one or more of the AI templates with a tenant enterprise from among the plurality of tenant enterprises, transforming a communication on a switching network associated with the tenant enterprise according to the one or more AI templates associated with the campaign object, and providing the transformed communication to a target legacy customer outreach platform of the tenant enterprise.

Embodiments are provided for anticipating a demand for transportation on demand vehicles operating in a geographical region of interest, including a non-transitory computer-readable medium including instructions that when executed by at least one processor, cause it to perform operations, which may include: determining a plurality of spatiotemporal service need feature vectors characterizing a transportation need in the geographical region of interest over a first time period; determine a time-resolved regression function based on the plurality of spatiotemporal service need feature vectors; applying the time-resolved regression function to determine, from the plurality of spatiotemporal service need feature vectors, a plurality of anticipated spatiotemporal service need feature vectors for a second time period, subsequent to the first time period; and using the plurality of anticipated spatiotemporal service need feature vectors to determine a measure of anticipated transportation need in the geographical region of interest for the second time period.

A system and method for displaying a plurality of tasks from a client device to a server device, wherein the client device, in response to an indication of availability from the server device, receives task data for each of the plurality of tasks, including information indicative of a valuation rate of each task determined via a client device, wherein the valuation may be a set value of a timer-related value. Actions by the server device regarding completion and/or cancellation of previous tasks can modify the valuation rate.

Systems and methods for managing change requests are disclosed. A system for managing change requests may include a memory storing instructions and at least one processor configured to execute instructions to perform operations including: receiving, from a client device, a change request; routing the change request to a first similarity determination pipeline, based on the first classification, identifying an implementation device; and transmitting the change request to the implementation device. The first similarity determination pipeline may be configured to: extract at least one first request element from the change request; determine a first group of change requests based on the at least one first extracted request element; determine a first similarity metric between the change request and the first group of change requests; and determine a first classification of the change request based on the first similarity metric.

A method of configuring robot fleets with additive manufacturing capabilities includes receiving a request for a robotic fleet to perform a job and determining a job definition data structure based on the request. The job definition data structure defines a set of tasks to be performed in furtherance of the job. The method includes determining a provisioning configuration for each additive manufacturing system based on the task to which the additive manufacturing system is assigned, the set of 3D printing requirements, the printing instructions, and the status of the additive manufacturing system. The method includes provisioning the additive manufacturing system based on the provisioning configuration and a set of additive manufacturing system provisioning rules that are accessible to an intelligence layer to ensure that provisioned systems comply with the provisioning rules. The method includes deploying the robotic fleet based on the robotic fleet configuration data structure to perform the job.

Systems and methods are disclosed for scheduling a workforce. In one embodiment, the method comprises receiving a shift activity template; receiving an association between the shift activity template and at least one worker; and scheduling a plurality of schedulable objects. The scheduling is performed in accordance with a workload forecast and schedule constraints. Each of the schedulable objects is based on the shift activity template. The shift activity template describes a worker activity performed during a shift. The template has range of start times and a variable length for the activity. The activity is associated with a queue.

A method of proactively defending combustible property against fire ignition and flame spread in the presence of wild fire. The method involves establishing wireless communication between a GPS-tracking anti-fire (AF) chemical liquid spraying system, and a wireless communication network supporting a network database. The GPS-tracking anti-fire chemical liquid spraying system is used to spray an environmentally-clean anti-fire chemical liquid over the exterior surfaces of a GPS-specified combustible parcel of property, and generating a GPS-coordinate and time/date stamped data records pertaining to the application of the environmentally-clean anti-fire chemical liquid spray over the exterior surfaces of the GPS-specified combustible parcel of property. The GPS-coordinate and time/date stamped data records are transmitted over the wireless communication network for storage in the network database. A computing system is used to access the GPS-coordinate and time/date stamped data records from the network database, so as to verify that the GPS-specified parcel of property has been fire-protected on particular date by virtue of the GPS-specified property being sprayed with the environmentally-clean anti-fire chemical liquid so as to proactively inhibit fire ignition and flame spread in the presence of wild fire.

A method for estimating a wait time associated with a queue serviced by active service points. The method comprises obtaining sensor data relating to the queue; from which a plurality of waiting entities occupying respective positions in the queue is identified, each waiting entity associated with a respective number of individuals; receiving a request to compute an estimated wait time (EWT) for a given one of the individuals; computing the estimated wait time for the given individual; and causing a message comprising the EWT to be made accessible to a communication device associated with the given individual. The EWT is computed based on: (i) a distribution, in terms of the number of individuals per waiting entity, of the waiting entities occupying respective positions in the queue ahead of the given individual; (ii) nominal wait times associated with respective numbers of individuals; and (iii) the number of active service points.