# US 11,443,513 B2 · Systems and methods for resource analysis, optimization, or visualization > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,443,513 B2 - Document ID: US11443513B2 - Status: Granted - Kind: B2 - Application number: 17/403,860 - Filed: 2021-08-16 - Published: 2021-12-02 - Granted: 2022-09-13 - Earliest claimed: 2020-01-29 - Applicants: Prashanth Iyengar - Inventors: Prashanth Iyengar - Web page: https://patentgrep.com/patent/US11443513B2 ## CPC - G06F 3/0481: based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance - G06Q 10/063114: {Status monitoring or status determination for a person or group} - G06Q 10/0633: Workflow analysis - G06Q 10/0637: Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals - G06Q 10/0639: Performance analysis of employees; Performance analysis of enterprise or organisation operations - G06Q 10/06393: {Score-carding, benchmarking or key performance indicator [KPI] analysis} - G06Q 10/06395: {Quality analysis or management} - G06T 7/0004: {Industrial image inspection} - G06T 7/0008: {checking presence/absence} - G06V 20/41: {Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items (segmenting video sequences G06V20/49)} - G06V 20/46: {Extracting features or characteristics from the video content, e.g. video fingerprints, representative shots or key frames} - G06V 20/52: Surveillance or monitoring of activities, e.g. for recognising suspicious objects (recognising microscopic objects G06V20/69) - G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202) - G06Q 50/04: Manufacturing - G06T 2207/10016: Video; Image sequence - G06T 2207/30164: Workpiece; Machine component - G06T 2207/30232: Surveillance - G06V 20/44: {Event detection} - G06V 2201/07: Target detection - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - 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 - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract A system and method for distributed surveillance of an area to monitor a process and visual effects of the process. Exemplary methods include, among others, asset effectiveness, issue identification and prioritization, workflow optimization, monitoring, estimation, verification, compliance, presentation, and/or identification for a given process. Such application may include, but are not limited to, manufacturing, quality control, supply chain management, and safety compliance. ## Claims ### Claim 1 A method of visualizing a process, comprising: receiving data from one or more data sources, including one or more cameras; analyzing the received data to identify one or more inefficiency events in the process; and visualizing the analyzed data, wherein the visualizing the analyzed data includes displaying a user interface on a display and the user interface includes a timeline of video segments and permits a user interface input to zoom in and out, wherein the timeline that is zoomed out provides an indicator of a total number of inefficiency events and corresponding time effect based on the total number of inefficiency events, and the timeline that is zoomed in provides a second indicator of the identity of the inefficiency event and an associated duration of the inefficiency event on the zoomed in timeline. ### Claim 2 (depends on 1) The method of claim 1, wherein the user interface includes a video segment from the one or more cameras based on the analyzed data identifying an identity of the inefficiency event. ### Claim 3 (depends on 2) The method of claim 2, wherein the user interface also includes a listing of a plurality of different video segments corresponding to different time segments having a same identity of the inefficiency event. ### Claim 4 (depends on 2) The method of claim 2, wherein the user interface also includes a listing of a plurality of different video segments corresponding to different time segments with each time segment being identified as any of a plurality of different identities of the inefficiency events. ### Claim 5 (depends on 2) The method of claim 2, wherein the user interface includes more than one video segment from two or more cameras based on the identity of the inefficiency event. ### Claim 6 (depends on 1) The method of claim 1, wherein the user interface comprises a plurality of timelines, wherein each timeline is associated with different data from different one or more data sources. ### Claim 7 (depends on 1) The method of claim 1, wherein the visualizing includes displaying a different user interface on a display and the different user interface includes displaying a graph of a metric generated from the analyzing the received data. ### Claim 8 (depends on 7) The method of claim 7, wherein the visualization includes receiving from a user an input corresponding to a location of the graph of the metric and displaying a video segment from the one or more cameras based on the received input. ### Claim 9 (depends on 7) The method of claim 7, wherein the visualization further includes displaying a series of video segments from the one or more cameras corresponding to time interfaces on the graph for instances in which the metric is above or below a threshold. ### Claim 10 (depends on 1) The method of claim 1, further comprising using analysis of the received data to distribute sensors, and the analysis of the received data identifies locations of inefficiency within the process, and the distribution of sensors is about the locations of inefficiencies. ### Claim 11 A method of visualizing a process, comprising: receiving data from one or more data sources, including one or more cameras; analyzing the received data to identify one or more inefficiency events in the process; and visualizing the analyzed data, wherein the analysis of received data comprises identifying an inefficiency, wherein an inefficiency is determined by an underutilized resource because of a branch in the process with one side of the branch creating a lag compared to another side of the branch. ### Claim 12 (depends on 11) The method of claim 11, wherein the analysis of received data comprises identifying a root cause of the inefficiency. ### Claim 13 (depends on 11) The method of claim 11, wherein the analysis comprises analyzing received data corresponding to a plurality of branches to identify a series of inefficiencies along the process at more than one branch. ### Claim 14 (depends on 13) The method of claim 13, further comprising providing an optimized process order in which at least one of the series of inefficiencies is reduced to improve an overall process efficiency. ### Claim 15 (depends on 14) The method of claim 14, further comprising receiving an input from a user and analyzing the received data to define and identify an inefficiency based on the input. ### Claim 16 (depends on 15) The method of claim 15, wherein the received input indicates a desired result including a reduction of resources, an improvement in process time, an improvement in resource usage, and combinations thereof. ### Claim 17 (depends on 11) The method of claim 11, further comprising analyzing branch points from an end of the process toward the beginning of the process to sequentially optimize the process. ### Claim 18 (depends on 11) The method of claim 11, wherein the visualizing includes displaying a user interface on a display and the user interface includes displaying a graph of a metric generated from the analyzing the received data, and includes receiving from a user an input corresponding to a location of the graph of the metric and displaying a video segment from the one or more cameras based on the received input. ### Claim 19 (depends on 18) The method of claim 18, wherein the visualization further includes displaying a series of video segments from the one or more cameras corresponding to time interfaces on the graph for instances in which the metric is above or below a threshold. ### Claim 20 A method of visualizing a process, comprising: receiving data from one or more data sources, including one or more cameras; analyzing the received data to identify one or more inefficiency events in the process; and visualizing the analyzed data, wherein the visualizing the analyzed data includes displaying a user interface on a display and the user interface includes a timeline of video segments and permits a user interface input to zoom in and out, wherein the timeline that is zoomed out provides an indicator of a total number of inefficiency events and corresponding time effect based on the total number of inefficiency events, and the timeline that is zoomed in provides a second indicator of the identity of the inefficiency event and an associated duration of the inefficiency event on the zoomed in timeline, and wherein the analysis of received data comprises identifying an inefficiency, wherein an inefficiency is determined by an underutilized resource because of a branch in the process with one side of the branch creating a lag compared to another side of the branch.