# US 12,001,990 B2 · Time and attendance system suitable for large or mobile work forces > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,001,990 B2 - Document ID: US12001990B2 - Status: Granted - Kind: B2 - Application number: 17/564,684 - Filed: 2021-12-29 - Published: 2022-04-21 - Granted: 2024-06-04 - Earliest claimed: 2019-12-19 - Assignees: Alt236, LLC - Applicants: Alt236, LLC - Inventors: Oliver Von Troll; Cheryl L. Doel; Vardan Karapetyan; Yerem Khalatyan - Web page: https://patentgrep.com/patent/US12001990B2 ## CPC - G06Q 10/06398: {Performance of employee with respect to a job function} - G06N 20/00: Machine learning - G06Q 10/105: Human resources - G06Q 30/0185: {Product, service or business identity fraud} - G07C 1/10: together with the recording, indicating or registering of other data, e.g. of signs of identity - G07C 9/25: using biometric data, e.g. fingerprints, iris scans or voice recognition - G07C 9/27: with central registration - G07C 9/28: the pass enabling tracking or indicating presence - G07C 9/38: with central registration - H04B 1/385: {Transceivers carried on the body, e.g. in helmets} - H04L 67/52: specially adapted for the location of the user terminal - H04W 4/021: Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences - G06Q 50/08: Construction - G06V 40/172: {Classification, e.g. identification} - G07C 9/37: using biometric data, e.g. fingerprints, iris scans or voice recognition - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G07C: TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE - H04B: TRANSMISSION - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) - H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract A system, method, and apparatus for managing and monitoring productivity on subjects within one or more worksites is disclosed. The system includes a computing device, and in some embodiments a wearable device, configured to collect data associated with an employee on the one or more worksites in real-time in addition to verifying the identity of an employee based on images of the employee captured on the worksite within a geofence in order to prevent fraudulent clocking in/out. The collected data is utilized to track the productivity or lack thereof of the employee on the worksite. ## Claims ### Claim 1 A method comprising: defining, by a server, a geofence corresponding to a worksite on which a first, employee and a second employee are assigned to work, the first employee assigned a first computing device and the second employee assigned a second computing device, the first and second computing devices each operable to collect employee specific (ES) data and communicate the ES data collected by the first computing device and the ES data collected by the second computing device to the server; wherein the ES data collected by the first computing device and the second computing device is incrementally stored in an offline employment activity reservoir configured to reduce power consumption of the power source of the first computing device and the power source of the second computing device during collection and transmission of the ES data; receiving, at the server, the ES data collected by the first computing device and the ES data collected by the second computing device, wherein the ES data collected by the first computing device and the ES data collected by the second computing device includes at least haptic data collected by the first computing device and the second computing device, respectively; verifying, via the server, an identity of the first employee based on the ES data collected by the first computing device; determining, via the server, that either the first employee is not, performing a first task assigned to the first employee based on the ES data collected from the first computing device at the server, or that the second employee is not performing a second task assigned to the second employee based on the ES data collected from the second computing device at the server, wherein the ES data collected is acquired within the geofence for a predetermined period of time; and responsive to the server determining that either first employee is not performing the first task or that the second employee is not performing the second task, the server generating a notification at an employer side user interface of the server. ### Claim 2 (depends on 1) The method of claim 1, wherein analyzing whether the first computing device is in the possession of the first employee comprises: comparing the haptic data collected by the first computing device with the haptic data collected by the second computing device; and determining, as a result of comparing the haptic data, a similarity between the haptic data collected by the first computing device and the haptic data collected by the second computing device. ### Claim 3 (depends on 2) The method of claim 2, wherein determining the similarity between the haptic data collected by the first computing device and the haptic data collected by the second computing device comprises determining a similarity in a heartbeat in the haptic data collected by the first computing device and a heartbeat in the haptic data collected by the second computing device. ### Claim 4 (depends on 2) The method of claim 2, wherein the ES data collected by the first computing device includes location data indicating a location of the first computing device at a given time, the ES data collected by the second computing device includes location data indicating a location of the second computing device at a given time, analyzing whether the first computing device is in the possession of the first employee comprises: comparing the location data of the first computing device with the location data of the second computing device; and determining, as a result of comparing the location data, a similarity between the location data of the first computing device with the location data of the second computing device. ### Claim 5 (depends on 1) The method of claim 1, further comprising: verifying, via the first computing device, the first employee is a live subject based on the plurality of identifiable features. ### Claim 6 (depends on 1) The method of claim 1, further comprising: storing training data that comprises a plurality of training instances, each of which includes a plurality of feature values; using one or more machine learning techniques to train a classification model based on the training data; identifying a first plurality of feature values associated with the first employee; based on the first plurality of feature values, determining whether the first employee is the second employee; and wherein determining comprises inserting the first plurality of feature values into the classification model that generates an output that indicates a plurality of productivity data associated with the first employee. ### Claim 7 (depends on 6) The method of claim 6, further comprising: storing training data that comprises the plurality of training instances, each of which includes the plurality of feature values; using one or more machine learning techniques to train a classification model based on the training data; identifying a second plurality of feature values associated with the second employee; based on the second plurality of feature values, determining whether the second employee is the first employee; and wherein determining comprises inserting the second plurality of feature values into the classification model that generates an output that indicates a plurality of productivity data associated with the second employee. ### Claim 8 (depends on 1) The method of claim 1, further comprising: storing locally, via the first computing device, a plurality of reporting actions associated with the first employee performed within the geofence of the worksite. ### Claim 9 (depends on 8) The method of claim 8, further comprising: uploading to the server the plurality of reporting actions associated with the first employee upon the server detecting a communicative coupling between the first computing device and a communicative network. ### Claim 10 A system comprising: a first computing device, including a power source, that is associated with a first employee and that collects employee specific (ES) data, and which transmits the ES data that is collected, wherein the ES data collected by the first computing device is incrementally stored in an offline employment activity reservoir configured to reduce power consumption of the power source of the first computing device during collection and transmission of the ES data; a second computing device, including a power source, that is associated with a second employee and that collects ES data and which transmits the ES data that is collected, wherein the ES data collected by the second computing device is incrementally stored in the offline employment activity reservoir to reduce power consumption of the power source of the second computing device during collection and transmission of the ES data; and a server configured to: define a geofence configured to be allocated to a worksite associated with the first employee and the second employee; receive ES data collected by the first computing device and ES data collected by the second computing device, wherein the ES data collected by the first computing device and ES data collected by the second computing device each include at least haptic data collected by the first and second computing devices; verify an identity of the first employee based on the ES data collected by the first computing device; subsequent to verifying the identity of the first employee, determine whether the first computing device is in the possession of the first employee based on the ES data collected by the first computing device and comparing it to ES data collected by the second computing device; and generate a notification at an employer side user interface in response to the server determining that the first computing device is not in possession of the first employee. ### Claim 11 (depends on 10) The system of claim 10, wherein the server is configured to analyze whether the first computing device is in the possession of the first employee by being configured to: compare the haptic data collected by the first computing device with the haptic data collected by the second computing device; and determine, as a result of comparing the haptic data, a similarity between the haptic data collected by the first computing device and the haptic data collected by the second computing device. ### Claim 12 (depends on 11) The system of claim 11, wherein the server being configured to determine the similarity between the haptic data collected by the first computing device and the haptic data collected by the second computing device comprises the server being configured to determine a similarity in a heartbeat in the haptic data collected by the first computing device and a heartbeat in the haptic data collected by the second computing device. ### Claim 13 (depends on 11) The system of claim 11, wherein the ES data collected by the first computing device includes location data indicating a location of the first computing device at a given time, the ES data collected by the second computing device includes location data indicating a location of the second computing device at a given time, the server being configured to analyze whether the first computing device is in the possession of the first employee comprises the server being configured to: compare the location data of the first computing device with the location data of the second computing device; and determine, as a result of comparing the location data, a similarity between the location data of the first computing device with the location data of the second computing device. ### Claim 14 (depends on 10) The system of claim 10, further comprising: a sensor communicatively coupled to the server configured to scan a plurality of identifiable features associated with the first employee; wherein the server is further configured to: compare the plurality of identifiable features to a plurality of topical identification content stored on a database communicatively coupled to the server; determine an identification similarity threshold associated with the first employee based on a stored established employee identification record; and flag the first employee based on the identification similarity threshold being exceeded by the plurality of identifiable features. ### Claim 15 (depends on 14) The system of claim 14, wherein the plurality of identifiable features is a subset of the plurality of ES data. ### Claim 16 (depends on 10) The system of claim 10, wherein the server is further configured to: store training data that comprises a plurality of training instances, each of which includes a plurality of feature values; use one or more machine learning techniques to train a classification model based on the training data; identify a first plurality of feature values associated with the first employee; and determine whether the first employee is the second employee based on the first plurality of feature values; and wherein the determination comprises inserting the first plurality of feature values into the classification model that generates an output that indicates a plurality of productivity data associated with the first employee. ### Claim 17 (depends on 16) The system of claim 16, wherein the server is further configured to: store training data that comprises the plurality of training instances, each of which includes the plurality of feature values; use one or more machine learning techniques to train a classification model based on the training data; identify a second plurality of feature values associated with the second employee; determine whether the second employee is the first employee based on the second plurality of feature values; and wherein the determination comprises inserting the second plurality of feature values into the classification model that generates an output that indicates a plurality of productivity data associated with the second employee. ### Claim 18 (depends on 16) The system of claim 16, wherein the first and second computing devices are configured to: store a plurality of reporting actions associated with the first employee or second employee performed within the geofence of the worksite. ### Claim 19 (depends on 16) The system of claim 16, wherein the first and second computing devices are configured to: store a plurality of reporting actions associated with the first employee performed within the geofence of the worksite. ### Claim 20 A wearable device comprising: a processor, a power source, and supporting circuitry configured to: collect a plurality of employee specific (ES) data associated with a first employee in possession of the wearable device; transmit, to a server communicatively coupled to the wearable device, the plurality of employee specific (ES) data associated with the first employee, wherein the plurality of ES data includes at least haptic data; receive, from the server, an indicator that the first employee is within a geofence defined by the server; receive, from the server, a verification of the identity of the first employee based on the plurality of ES data; wherein the plurality of ES data is incrementally stored in an offline employment activity reservoir configured to reduce power consumption of the power source during collection and transmission of the plurality of ES data; and receive, from the server, a determination that the first employee is not in possession of the wearable device based on the plurality of ES data.