Data Processing Applications TRIZ Cases

V-grooves and centering guides speed pizza cutting while keeping slice sizes uniform to reduce waste and support accurate nutrition reporting.

Multi-sensor motion tracking detects prayer units and positions, then alerts users to prevent missed counts and improve session accuracy.

Mobile location data predicts arrival time to tune HVAC setback recovery and hot water volume, cutting energy waste and short cycling.

Remote supervisory control replaces USB-based kitchen equipment updates, cutting multi-site menu and firmware rollout effort.

Prediction environment data and facility models are used to simulate power use and automatically build stable energy-saving control scenarios.

A brushroll, suction nozzle, and vacuum airflow work together to avoid carpet saturation while improving fluid recovery and debris removal.

RFID stain markers preserve item and stain location in laundry piles, enabling targeted pretreatment and machine-specific wash settings.

Dynamic module queues let beverage steps run concurrently, reducing idle resources and increasing throughput beyond FIFO production.

Dynamic workstation displays update by item position to keep food assembly accurate, efficient, and visible to customers.

Weight, shape, and terahertz sensing validate deposited shipments in lockers, reducing fraud, delivery errors, and manual checks.

Individually addressable food holding modules enable remote reconfiguration and faster recovery after outages to reduce spoilage and retrofit costs.

Magnetic cover retention and automatic release keep sushi plates clean while removing manual cover handling and table clutter.

A visual environment map links each sensor reading to its physical location, making multi-sensor monitoring easier to interpret.

Cryptographic authentication and electronic lock control secure distributed mail boxes while enabling authorized pickup and delivery confirmation.

A fluid-controlled bladder tilts the support surface to create safe instability that engages core muscles and helps prevent atrophy.

A visual map links each sensor reading to its real location, replacing hard-to-read tables and improving multi-sensor monitoring.

3D point clouds, neural detection, HD maps, and V2V data help smart cars handle urban obstacles and human driving behavior safely.

A centralized server shares stolen vehicle data and proximity alerts, widening search coverage while reducing reliance on law enforcement.

A load-priority controller keeps total power below utility demand thresholds by selectively energizing critical and non-peak loads.

Iterative PLP placement combines striking distance with terrain-aware layout to protect tall mountain wind turbines with fewer protectors.

A linear scheduling model coordinates wind power, gas generators, and compressors to handle wind fluctuations while cutting offshore platform carbon emissions.

Converts vehicle CO2 reduction into forest-like contribution displays, making driver impact intuitive and improving engagement.

A digital platform sets recyclate feed content from recycling and plant data to balance material availability, emissions, and product performance.

Boot-up diagnostics verify ECU read/write protection settings automatically, cutting manual checks and flagging unsafe access states.

Dynamic wait times for candidate autonomous vehicle pickup points help riders choose less congested locations and improve pickup flow.

SVD-based grid model estimation helps converters track changing grid dynamics and improve stability under renewable variability.

Identification tags and server data guide impurity removal and conductor sorting, enabling high-purity wire reuse without energy-intensive refining.

Adaptive audible and visual cues help autonomous vehicles guide users to precise pickup points based on map context and response sensing.

Obstacle-aware self-driving scooters travel to user pickup points, improving PMD availability while reducing sidewalk clutter and search time.

Health, trip, traffic, and weather data are combined to score driver risk and restrict vehicle operation or trigger ride-sharing when needed.

SCADA voltage data and machine learning link momentary outages to likely sustained outages, speeding grid analysis without AMI.

RFID-based player and chip reading flags mismatches between table location and token holder records to improve fraud detection and tracking accuracy.

A dynamic-adaptive dispatch model balances thermal and renewable generation to cut curtailment, stabilize the grid, and reduce losses.

An ESS tied to building switchgear shifts stored power into peak periods to curb grid spikes, cut time-of-use costs, and ease balancing demand.

Standardized sensor interfaces and virtualized control algorithms cut vendor lock-in while enabling granular real-time energy distribution in data centers.

Weak-node screening and N-2 fault analysis guide static and dynamic reactive power compensation for stable, lower-cost offshore wind grid connection.

Distributed transformer sensors capture broadband defect signals and use synchronized timing to locate SWER faults before outages or fire risk.

Machine-learned safety scoring and trajectory prediction help autonomous vehicles detect unsafe pickup or drop-off paths and trigger mitigation actions.

A controller-based microgrid simulation models route inputs, outputs, and device failures to predict interactions and improve power delivery resilience.

Connector rivets and stacked electrode routing help compact analyte sensors maintain stable electrical contact and reduce shorting risk.

A controller-driven microgrid simulation models route-based power inputs and outputs to predict device interactions and support failure response.

Historical SAIDI and ASIDI thresholds guide feeder switchovers so impacted grid sections move to more reliable feeders serving critical loads.

Dynamic waypoint and circuit assignment prepositions autonomous vehicles to reduce latency, improve coverage, and balance demand.

Priority and rules engines rank mission requests, assign vehicles and personnel, and pre-load map data to keep AV fleets ready under changing conditions.

Hierarchical nonlinear and mixed-integer optimization splits load across device groups to improve power network scalability and computing time.

Plans isolated switch sections around distributed power sources to restore more customers faster and shrink outage areas after grid accidents.

Predicted energy use triggers a schedule for normal and power-saving days, helping an electronic apparatus stay within a target budget.

A controller switches PV power between building loads and the grid using network capability data to raise self-consumption without overloading supply.

Sub-hourly nodal and weather-linked carbon scoring improves true grid offset accounting and renewable integration efficiency.

Multiple tire parameters are combined to detect structural changes and output the right maintenance instruction for each tire state.

Camera-based object detection verifies bin presence and collection status at each stop, reducing missed pickups and route inefficiency.

Routes autonomous vehicles away from crowded pickup and drop-off spots by predicting pullover congestion within ETA windows.

When one vehicle misses a scheduled task, the controller reassigns a lower-priority vehicle to keep high-priority work on time.

Weather forecasts, source availability, and thermal storage are combined to cut carbon and energy costs while maintaining home comfort.

Dynamic in-transit cooking adjusts time, temperature, and humidity to keep delivered food hot and freshly cooked on arrival.

Reinforcement learning maps grid state data to dispatch actions, speeding real-time scheduling under uncertainty and large control scale.

Sensor and map data let an autonomous vehicle detect pickup queues, join appropriately, and reduce disruption to other road users.

Crew-aware outage scheduling improves estimated repair times by combining outage priority, crew hours, availability, delays, and reserve capacity.

Continuous event monitoring detects faults in energy storage units, triggers automatic corrective actions, and speeds maintenance response.

Ride-hailing users are matched to nearby autonomous vehicles for simple maintenance tasks, cutting engineer dispatch time and manpower.

Color patterns with different sensitivities let a tire repair patch reflect real UV, heat, and oxidation aging more accurately than printed expiry dates.

Historical wait-time prediction lets autonomous vehicles handle intermediate stops without idle waiting, improving fleet use and pickup timing.

By reusing proof-of-work outputs as random values, auxiliary loads cut RNG energy use while helping stabilize renewable-heavy power grids.

Weak-node voltage indices identify where static and dynamic reactive power support should be placed to stabilize offshore wind-connected grids at lower cost.

Vehicle sensor data is turned into visual risk maps that show which parts are most at risk and how drivers can reduce damage.

An autoencoder-based virtual sensor tracks dissolved oxygen in aquaculture and updates for drift, cutting sensor cost and maintenance.

Multiple machine learning models and deviation checks improve non-destructive steel property evaluation when input conditions fall outside a suitable model.

By separating guest-carried mobile terminals from installed wireless terminals, this case improves venue congestion measurement accuracy.

Physics-based electromagnetic scene simulation generates labeled synthetic imagery, cutting manual collection and labeling for AI detection systems.

Offline meeting feedback is captured after detected in-person dates to refine match recommendations, profiles, and user tips.

Software containers isolate user data in a zero-knowledge social network, enabling private sharing and lower computational burden.

OCR and machine learning link patent drawing numbers to descriptions, enabling faster figure-based search and intuitive access to related text.

Body-anchored AR messaging uses body tracking, spatial UI, and voice input to speed hands-free message access while limiting visual clutter.

Specialized legal, financial, and technical agents are orchestrated to resolve document-analysis conflicts with less computation and fewer versions.

A terminal coordinates sessions with property and 3D image servers so authorized users can access tacit knowledge models with less workflow friction.

Scanned sender data and OCR let users trigger predefined mail actions automatically, improving incoming mail control with less waste.

Actuation counts from safety functions are used to rate worker awareness and tune machine restrictions to balance site safety and productivity.

ML-based scheduling predicts well failures and updates job priorities to allocate oil field resources with less downtime and network risk.

Tidal current speed and direction are combined with gear location signals to estimate lost fishing gear positions with fewer false alarms.

Multiple RFID readers log chip movement inside the cage and at exits to detect fraud and maintain accurate casino chip transfers.

Rule-based digital detective logic and scope enforcement reduce false positives while keeping investigative outputs explainable and jurisdiction-bound.

Projected reference lines from a mini PC and smartglasses replace paper drawings and manual marking to improve installation accuracy on site.

A staged AI workflow turns short invention descriptions into claims and full applications, cutting drafting time while supporting legal compliance.

Selective data-structure updates and session formatting keep distributed devices synchronized while limiting bandwidth and network overhead.

Net load profiles plus local weather data reveal unregistered PV, EV charging, and storage behind the meter without extra metering.

Generative AI automates assessment, coaching plans, and on-demand sessions to scale executive function support for children with learning disabilities.

Sensor and body-temperature data are analyzed with AI to flag avian influenza risk in real time and improve alerts through user feedback.

Context selection from neighboring and co-located luma blocks improves chroma intra prediction signaling efficiency under AV1 SDP partitioning.

Geofenced map views and color-coded caller indicators help PSAPs locate mobile emergency sessions across jurisdictions faster.

Spatiotemporal graph analysis flags shielded or altered license plates by matching travel patterns and mutually exclusive time-distance nodes.

AI vision and risk scoring adjust proctoring by test taker and location to curb cheating, proxy tests, and unnecessary monitoring cost.

Automated sensor fusion and machine intelligence detect and track marine mammals in real time, reducing pile driving delays in poor visibility.

Image comparison and access-event data detect incident scene contamination, identify likely entrants, and trigger workflow changes.

User-corrected AI outputs are fed back into the model to improve response accuracy while cutting data preparation and training time.

A secure portal uses retrieval-code identity checks and electronic acceptance to deliver legal documents with verifiable proof of service.

Real-time AI adapts remote learning content, assessments, and resource delivery to each user profile for stronger engagement and outcomes.

Selective privacy dashboards and disclosures show people what surveillance data is recorded and used without weakening building security.

Real-time interprocess messaging adjusts wagering opportunities and odds from betting patterns, improving risk balance and wager handling accuracy.

Power-aware rebuilding targets selected virtual segment portions, cutting rebuild overhead while preserving parallel query performance.

Historical sub-period electricity patterns are used to adjust target energy proportions, improving allocation accuracy under generation fluctuations.

Vehicle speed, turns, and boundary data reveal field entry and loading points, improving route planning while reducing fuel use and soil compaction.

Bayesian decline curve analysis automates EUR updates from clustered well production data while improving consistency and uncertainty handling.

Construction data is split into structural and geometry sets so suppliers can work efficiently while providers keep geometry confidential.

Real-time access point status and visitor location feed an AI route engine to guide people through complex buildings with clearer navigation.

CV and NLP extract menu text, flag non-compliant ingredients, and generate dietary-safe menu options without staff intervention.

When a shared post leads to paywalled or inaccessible content, the system verifies access first and serves alternatives or summaries.

Multi-source sensing separates main crops, weeds, snow, and dormancy to estimate cover crop duration and generate ICCI for farmer incentives.

Personalized service matching, feedback loops, and self-service tools help reduce dependency cycles and close resource gaps.

An autoencoder flags non-technical losses in distribution network consumption data without costly inspection-based training sets.

Verified engaged fan input improves artist collaboration recommendations by filtering spam and raising suggestion accuracy.

Multi-sensor gas data is analyzed to identify abnormality causes quickly and trigger automatic valve closure for safer indoor gas management.

Recorded cross-slope data is reused by GPS position to auto-adjust paving or milling passes, reducing human error and 3D survey cost.

Multiple live sports feeds and third-party wager data are combined in an HMD view, reducing channel switching and simplifying bet comparison.

Continuous sensor and activity data modeling keeps insurance policies aligned with changing user behavior while reducing manual update delays.

AI-based camera screening turns a doorbell into a security hub for visitor recognition, parcel theft alerts, and intrusion detection.