Data Processing Applications TRIZ Cases

See how an imaging work station captures dose images and weight data simultaneously to enable r

See how multi-image capture and cross-validation correct misrecognized clothing care symbols, e

See how store-specific data—business type, cooking tools, oil type, sales, and operating hours—

See how a server-based recipe system generates tailored cooking instructions by matching food p

See how component identification tracking at multiple time points enables traceability of refri

See how a camera and processor detect food introduction or removal, then provide real-time feed

See how camera-based item recognition and user authentication establish ownership relationships

See how a management server analyzes extraction operations and bin fullness over time sections

See how a virtual space server and IoT server coordinate cooking information transmission acros

See how a food management tag with a variable part translates food quantity into a measurable v

See how merging freezer temperature control into the vehicle infotainment terminal reduces devi

See how a waffle maker uses motion sensors to pre-heat only when users approach, reducing energ

See how a dispenser system aligns product depletion dates with battery depletion dates by adjus

See how a digital twin combines physics models and neural networks to complete missing well dyn

See how ML models trained on sensor data assess individual chiller efficiency in multi-unit pla

See how a display device recognizes food ingredients from refrigerator images and automatically

See how AI models determine garment management necessity, predict completeness across modes, an

See how an IoT-enabled toilet seat with a reminder button and sensor system sends real-time ale

See how a BMS simulates emission impacts at discrete time points to determine optimal implement

See how residual water temperature sensors and multi-level notifications prevent washing machin

See how a lightweight reusable container with interchangeable panels and drainage replaces heav

See how a refrigerator processor enables users to silence continuous abnormal-state notificatio

See how occupancy monitoring and visual urinal indicators reduce queue times by steering users

See how multi-agent reinforcement learning replaces experience-based control to reduce temperat

See how a network-connected prediction model detects frost accumulation and automatically sets

See how a control device adjusts steaming and post-processing conditions based on printed matte

See how electromagnetic wave-based arrangement estimation and candidate filtering reduce buildi

See how a lockable measuring module captures weight and size parameters during deposit to deter

See how pattern analysis and feedback loops automate reservation time recommendations, reducing

See how a cubby unit uses processing circuits, transparent doors, and LED lights to verify cust

See how a server diagnoses low water pressure and inadequate supply in ice-making appliances by

See how a clothing management apparatus predicts completeness for multiple modes, generates exp

See how image-based detection devices automatically classify food items and track consumption l

See how mobile racks with bay-level sensors and dynamic locking enable automated inventory trac

See how motorized seating arrangements use sensors and feedback to automate participant transit

See how an educational station system uses intermediary management and feedback channels to ena

See how optical address recognition and electronic locking merge multiple mailboxes into one ce

See how machine learning estimates optimal CA gas injection for perishable transport, balancing

See how mount sensors and duration tracking prompt users for water tank cleaning based on usage

See how an automated seating controller replaces manual coordination with motorized rotation an

See how activating hot water boilers stores excess solar energy as thermal reserves, raising se

See how a valve unit routes working fluid by temperature to enable both power generation and th

See how a spring-biased suction nozzle maintains surface contact while integrating fluid delive

See how an electronic apparatus coordinates unit functions across networked devices to deliver

See how a modular grill selection method evaluates face velocity, pressure loss, and noise to s

See how a server converts cycle history data from existing appliances to enable immediate AI co

See how mobile device geo-fencing predicts user arrival to optimize HVAC setback temperature an

See how RFID-based electronic documentation captures preparation, performance, and post-process

See how a mobile terminal provides ingredient recommendations and recipe feedback to balance us

A twist-lock brushroll, spring-loaded nozzle, and modular power cord improve maintenance, surface contact, and fluid recovery in upright deep cleaners.

Temperature sensing and demand forecasting estimate heat accumulator charge state, cutting premature charging and no-load heat losses.

Mobile location data predicts arrival and occupancy to precondition HVAC and hot water, cutting energy waste and short cycling.

RFID-based pharmaceutical cold storage verifies expiry, authenticity, and inventory while alerting staff to temperature or power faults.

Optimized gantry angles and patient support motion improve tumor dose placement while limiting healthy tissue exposure.

Customer-count detection lets a fryer raise oil standby temperature during busy periods and lower it off-peak to balance response time and energy use.

Patient-specific motion pattern matching detects true bed-exit attempts more accurately and triggers timely fall-prevention actions.

Perforated sections split liquid refuse from monetary donations, enabling secure public collection with less tampering and easier fund retrieval.

Sensors, imaging, and a manipulator organize clothing, prevent mildew, and enable remote outfit selection without manual searching.

Utility-state signals let a water heater adjust setpoints and shed loads to cut peak-hour energy use and lower bills.

A central server compares reheating versus transfer cost so interconnected water heaters share excess hot water and cut cooling losses.

Vehicle data is split into approval-required and automatic streams so sensitive information reaches the data center only with driver consent.

Dynamic selection and combined execution of multiple AI modules improves autonomous vehicle control reliability without running all networks continuously.

Disaster-informed contingency estimation updates control tables for earthquake and tsunami failures to help prevent large-scale blackouts.

A neural network predicts likely manual takeovers and prompts driver reassurance to keep automated driving active longer.

Parking-risk data and towing detection help vehicles warn drivers, document evidence, and suggest lower-risk parking locations.

Server notifications identify autonomous vehicles near communicable cars, reducing misrecognition and collision risk in mixed parking areas.

Drone image capture and server control help tractors locate, align, and couple with trailers automatically, cutting driver effort and coupling time.

Longitudinal acceleration replaces speed-based UBI metrics to score rapid acceleration, braking, lane changes, and vehicle-specific risk.

Guided rack BMS voltage and temperature checks automate energy storage installation verification, cutting worker errors, delays, and rework.

An implantable identification chip uses oxide semiconductor transistors and onboard sensing to cut power use while maintaining reliable biometric authentication.

Displays train schedules and transfer details inside the vehicle so passengers can check connecting transport without using a separate mobile device.

Wireless light and sound alerts from the battery holder help users find shared electric vehicles at stations, even at night.

Multiple cameras identify an approaching vehicle user early, giving time to retrieve personalized photos and display them only in safe driving contexts.

Oil change detection and oil type confirmation let hydraulic excavators apply the right thresholds for more accurate abnormality judgment.

Dynamic chatrooms connect nearby drivers by road context and motion to clarify intent in merging, stops, and lane changes.

Condition-based sensor cleaning uses availability and environment data to preserve vehicle sensor function while reducing fluid waste.

Pre-authenticated head unit workflows cut repeated inputs for secure transfers, reducing driver distraction and cognitive burden.

Daily vehicle-level battery analysis with queue-based scheduling reduces storage load peaks while keeping multi-vehicle data processing efficient.

Selectable circuit symbols and live signal values help technicians diagnose vehicle wiring and components faster without extra downloads.

By comparing pedal speed, wheel speed, and motor torque, this case detects low tire pressure without separate sensors and helps prevent e-bike malfunctions.

Laser-irradiated and plated antenna regions are embedded in injection-molded housing to keep a smooth exterior while maintaining stable wireless communication.

Encrypted W2G delivery lets casino players securely sign, retrieve, and verify jackpot tax forms without manual pickup or paper loss.

Charging and discharging limits are raised during disasters or outdoor events to speed power supply and charging without using high battery stress all the time.

Distributed modules and broker caching handle high-capacity battery data faster while reducing maintenance load and keeping operation running after failures.

Manifest-based offloading lets autonomous vehicles verify data integrity across data centers and service stations despite limited bandwidth and storage.

Machine learning phantom meters estimate missing grid measurements from topology and history to detect faults and anomalies in unbalanced distribution systems.

An HVDC link with AC/DC and VSC control stabilizes direct renewable-to-load power supply despite intermittent generation.

Automatically maps electrical nodes to generate LOTO steps, cut manual tracing, and reduce unnecessary locks on shared EIDs.

Multiple user storage units are coordinated under a contracted supply period to deliver enough power for stable, reliable grid support.

Synchronized audio prompts and glove box lighting guide shared-vehicle users to handle an electronic key correctly in low-light conditions.

Standardized sensors and control algorithms coordinate energy sources and loads for granular data center load shedding and faster integration.

Distributed software management modules use publish-subscribe power states to cut cockpit control load and reduce faults in vehicle operation.

Telematics, AI, and geofencing detect theft, vandalism, accidents, and relay attacks early, then alert owners or authorities in real time.

Abnormal events are detected quickly by classifying logs locally and sending only matched fault data, reducing communication and database load.

Aggregating multiple energy storage devices under contracted power dispatch helps stabilize grid supply when individual stored energy is insufficient.

When upcoming road sections fail autonomous driving conditions, the vehicle moves into a parking waiting area to avoid risky driver takeover.

Combining culvert water levels with roadbed pressure and moisture data improves flood-season road safety assessment and unattended monitoring.

Sensor fusion and behavior prediction help autonomous vehicles identify the right rider and guide them to the pickup point with accessible cues.

Automated topology discovery and policy-recipe workflows simplify vehicle diagnostics and configuration while reducing downtime and manual setup.

Precalculated diagnosis indicators from accumulated battery data enable fast battery assessment without extra charging or discharging steps.

Maps machine trajectories with terrain and object data to reproduce multi-machine worksites and reveal contact accident risks.

Sensors track cabin condition changes to predict passenger needs and alert crew early, cutting service delays and manual monitoring.

Synchronized blinking on the vehicle display and user terminal helps riders quickly identify their assigned autonomous taxi in crowded pickup areas.

Broadband sensing at SWER transformers uses extracted signal timing to locate early line defects, reducing inspection cost and fire risk.

Adaptive audible, visual, and digital cues help autonomous vehicles guide users to precise pickup points with less confusion and delay.

Timed vehicle monologue messages explain autonomous driving actions to riders and pickup users, reducing confusion without overloading them.

Sensor data and trained models help autonomous vehicles detect pickup queues, predict wait times, and join or avoid lines without blocking traffic.

SVD-based grid model estimation identifies dominant dynamics from input data, helping grid-connected converters stay stable under renewable variability.

A centralized virtual power plant coordinates storage and distributed resources to absorb excess solar and support peak grid demand.

Real-time control uses sensor data and precomputed operating regions to keep renewable sources near peak power as conditions change.

Distance-triggered external notifications help autonomous vehicles identify pickups and share clearer passenger cues with added context.

Autonomous vehicles with locking lockers and user authorization replace fixed hubs, enabling secure package pickup, returns, and dynamic routing.

Automatic battery state-data transmission to a management server prevents backup loss, cuts site visits, and supports remote failure diagnosis.

Real-time state estimation and machine learning turn contingency data into a security index that predicts power system failures before outages escalate.

Vehicles are parked early, then moved to the pick-up area near scheduled usage time to cut passenger waiting and ease parking lot flow.

Sensor and map data score passenger pickup or drop-off paths, letting the vehicle change trajectory or block door opening when conditions are unsafe.

Real-time impact, weight, and process data adjust driverless vehicle commands to limit movement deviation during manufacturing.

Separated QR codes on different cell surfaces keep battery identification readable even when one code is hidden or damaged.

Dynamic chatrooms link nearby drivers by distance, direction, road, and speed to clarify intent and reduce misunderstandings while driving.

Hierarchical road, lattice, and crossable dipole graphs improve autonomous driving plan accuracy while limiting map data complexity.

Real-time load micro-adjustments smooth grid demand, cut reserve buffer waste, and maintain reliable power supply.

Driving scores based on fuel efficiency and traffic violations unlock vehicle display themes, rewarding safer driving without extra fees.

Baseline power models and adaptive feedback help isolate faults across network levels, cutting false alarms, energy waste, and downtime.

Advance utility scheduling lets home appliances run in future time windows, cutting peak demand, energy costs, and brownout risk.

Blockchain storage and SHA1-based image processing help protect photovoltaic power data from tampering during transmission.

Dynamic in-vehicle chatrooms let nearby drivers share intent by distance, direction, and road context to reduce misunderstandings.

Integrated certified metering and secure communication support real-time two-way energy billing, dispute reduction, and small prosumer access.

Voltage time-series clustering identifies grid phase connections despite limited data, improving control reliability and reducing manual checks.

Stored-energy estimation and threshold checks help battery systems avoid unmitigated grid frequency deviations during regulation service.

Fleet consumption data pinpoints route sections with excess fuel use, then the control unit limits speed or gearing only where needed.

Real-time thermal modeling detects cold spots in semiconductor gas lines and guides heater control to prevent clogging and wasted energy.

Routes are replanned by matching each vehicle's sensor category to travelable areas, avoiding weather-driven detection limits and critical states.

Mobile acknowledgement and security-code access let casinos deliver W2G jackpot forms electronically while reducing replacement requests and data exposure.

A GAN predicts feeder layouts from mixed image sources to map overlapping pole assets and infer underground grid connections.

Adaptive horn, light, and notification cues help riders find an autonomous vehicle more precisely during pickup and drop-off.

A control device splits load variation between programmable sources and storage to stabilize grid frequency while preserving storage capacity.

By matching speech context, sentiment, and intent tags to stored emojis, the system builds composite emojis that better express nuanced user meaning.

Comparing monitoring data across vehicles helps assign monitors by risk and workload, reducing continuous watch stress while maintaining coverage.

Cameras match vehicle license plates to a media-playback device, enabling real-time parking alerts and automated check-in.

Remote work vehicles report travel status, position, and images so stranded conditions can be detected early and rescue can be coordinated quickly.

A scoop, pusher pads, and autonomous mapping let the robot collect and store tennis balls, cutting manual retrieval time and court hazards.

Specialized AI agents automate MES setup from text requests, cutting manual effort, errors, and scaling limits in complex factories.

Time-linked 3D terrain data helps work machines recognize cliffs early, avoiding productivity loss from unrecognized site edges.

Remote drone sensors assess crop and worksite readiness ahead of harvest, enabling timely harvester control with less damage and delay.

Sensor data and AI models detect fuel storage anomalies, rank risk, and trigger workflows to reduce manual wetstock errors.

Image and environmental data are combined to predict gas tank aging and damage, enabling timely maintenance with less manual inspection.

A building resource server allocates corridors, elevators, and passage rights to multiple robots to cut waiting, conflicts, and retrofit needs.

Automatically identifies factory material flow routes from P&ID diagrams and generates bypass paths around malfunctioning equipment to cut downtime.

Adaptive pet drinking demand control adjusts pump output by pet type while monitoring operating faults for safe remote water dispenser management.

Natural-language AI customization and tenant isolation let manufacturers tailor cloud MES and analytics without sacrificing reliability.

Generative AI helps industrial users self-configure data collection, analytics, and reporting without sacrificing SaaS reliability.

Production, model, and equipment data drive adaptive sampling rules that target high-risk parts while reducing inspection labor and cost.

Recognition sensors detect outside vehicles blocking an assigned exit space, enabling reallocation or vehicle slowdown to keep valet parking flow stable.

A neural network ranks tool-group KPIs and bottleneck output variation to cut work-in-process and shorten cycle time in complex fabs.

Device ID and state tracking let unmanned moving objects detect abnormalities early and route maintenance without interrupting operation.

Discrete Markov Chain and MCMC simulations predict asset degradation, RUL, and failure probability even with limited historical sensor data.

A modular Industrial IoT adaptation workflow reuses existing production lines across products, cutting development cost and compatibility issues.

Virtual production simulation checks manufacturing data for abnormalities and malware before release to physical equipment, avoiding system changes.

Machine learning isolates the most predictive signals, sets operating targets, and flags pre-error states to reduce industrial equipment downtime.

Uses graphical Lasso and constrained independence tests to find causal sequences across many factors with lower computational overhead.

Preprocessed alliance records add relationship type and strength to online communications, improving contact filtering while limiting data overhead.

Interaction-tracked search history is turned into graphical relevance views, helping legal researchers quickly resume work after breaks.

Multi-factor utterance analysis scores policy violations using pronouns, proper nouns, and anaphoras to rank corrective actions.

Historical rider behavior and current location are used to prefill destination choices, cutting interface steps and device resource drain.

A gesture-based voting interface lets shared-workspace users rank content so the server can reorder, annotate, or remove items with less manual editing.

Groups VOD items with identical access information into one visual selection unit, improving browsing and access without cluttering the interface.

Field surveys across growth stages quantify weed density and dominance, enabling targeted control that cuts herbicide use and pollution.

Employee review inputs are converted into structured coaching cards, helping companies apply training content in daily work with less manual analysis.

ML-generated trial content uses protocol data and feedback loops to speed clinical recruitment while improving tailoring and compliance.

Quantify greenhouse CO2 absorption and supply use rate to compare exhaust-gas sources, emissions reduction, and construction economics.

Optimization algorithms schedule shared assets across hydrocarbon projects to cut planning time, reduce asset use, and improve revenue.

Multi-source data fusion and neural network labeling turn complex equipment monitoring data into portraits for clearer status tracking and failure detection.

Virtual numbers give fans dedicated communication paths and access to artist-terminal history, addressing passive replies and missing read confirmation.