Data Processing Applications TRIZ Cases

Time-synced driving records and image replay make autonomous vehicle accident causes clearer for responsibility analysis and insurance handling.

Kalman filter and Gaussian correction estimate battery charge-discharge curves in real time, improving efficiency diagnosis across varied battery conditions.

Multiple antenna stop points are averaged to improve construction site positioning accuracy while handling signal interruptions and transmission errors.

Combining cameras, sensors, and beacon positioning, this case shows how unsafe driving is detected in real time and remediation messages are sent.

Active network components switch to user-premises or renewable power during grid outages to extend service continuity and reduce battery drain.

Multi-device atypical data is analyzed on a server to validate dangerous transport events, determine severity, and speed response without on-site investigation.

Mechanical crop sensors and Kalman filtering correct GNSS row-position errors, improving guidance line accuracy for later field passes.

Injecting known-frequency power signals from controllable assets reveals DER topology and impedance through voltage perturbation analysis.

Hydraulic pressure slope monitoring confirms bulk material delivery from a dump truck bed without manual signed proof, saving driver time.

Map-based line diagrams combine changing thickness, arrows, and color shading to track grid flow, voltage, and anomalies in real time.

A layered secondary power O&M platform unifies cross-zone data collection to eliminate silos, duplication, and incomplete equipment information.

Geospatial, distance, gas, and wind checks validate safe refueling conditions before opening the fuel valve to reduce fire and spill risk.

Operating data from home entertainment equipment is converted into a responsivity index to estimate whether a user can respond to external requests.

Semi-supervised clustering and classification refine transient voltage stability labels, reducing fixed-threshold bias and improving assessment reliability.

Two movement permission areas let an autonomous vehicle approach normally, then cross a white line only near the target space for valet parking.

Distributed vehicles export power through coordinated control and inversion to cover peak grid demand without new plant construction.

Location and ride-completion data trigger post-drop-off safety alerts, directions, and emergency assistance for autonomous vehicle passengers.

A unified control unit coordinates loading doors, boarding doors, and vehicle movement to simplify mobility device boarding and unloading.

AI predicts facility demand peaks from live and historical load data, then curtails contributing loads to cut utility demand charges.

Two-plane sequence signatures identify grid fault type and faulted phase accurately under weak-infeed conditions without extra hardware.

A representative autonomous taxi coordinates destination setting and billing across grouped vehicles, reducing repeated steps for rider groups.

A management server shares and activates vehicle digital keys for drivers and mechanics while restricting authority, blocking misuse, and keeping traceable records.

Node-specific activation and delay help distributed energy storage meet grid balancing needs while improving commitment reliability.

Real-time telemetry monitoring detects sensor and actuator failures early, enabling corrective mitigation without heavy onboard computation.

Sensor-based winding data is recombined across cores to train models that detect defect signs early and pinpoint the faulty core.

Voice recognition and passenger opinion checks let van riders request climate or media changes without distracting the driver.

Future demand prediction sets charge-state limits so grid storage keeps reserve power for later imbalances and avoids energy loss.

Dynamic workflows trigger location-specific driver tasks and evidence capture, reducing manual compliance management across regions.

IoT event data helps route post-disaster alerts to the right contacts, improving contact success while limiting communication occupation.

Autonomous IP packets from grid elements improve secure real-time data exchange, grid stability, and energy settlement accuracy.

Usage-based monitoring predicts RV asset status changes during a trip and adjusts vehicle operation before malfunctions cause disruption.

Kalman-filtered charge-discharge curves update OCV and impedance in operation to estimate battery efficiency degradation without long tests.

Voltage-polarity feedback shifts second switch turn-off toward zero inductor current, cutting body-diode loss in DCM power conversion.

By tracking RV asset usage and predicting status changes during a trip, the system can adjust vehicle operation before failures disrupt travel.

By prioritizing high, medium, and low loads, the controller keeps demand below utility thresholds and avoids higher peak energy charges.

A PID-Lagrange collaborative scheme regulates local loads using voltage data only, balancing voltage stability, cost, and user privacy.

Built-in GPS, magnetometer, and accelerometer data distinguish driver phone handling from passenger use and create logged evidence.

Fleet logic predicts stopover wait time and assigns parking, maintenance, or short trips to cut idle time without missing passenger pickup.

Multi-agent MADDPG coordinates thermal units and large-scale energy storage to handle grid frequency deviations with faster, more accurate control.

Distributed energy management adjusts fuel cell and DC/DC converter operating points from battery charge state to prevent overcharging and extend lifespan.

Real-time facility load adjustments smooth grid peaks and valleys, cutting power buffer waste, fuel use, and response delays.

Sensor-derived map data identifies roadside ramp structures so vehicles can guide passengers to easier entry points without onboard ramps.

Battery state prediction that combines driving, weather, and traffic data helps route EV drivers to the nearest suitable charging station.

Slot ID matching links shared digital keys to stored vehicle profiles, enabling automatic profile switching across multiple devices.

Vehicles charge each other during route overlaps, cutting charging-station detours and preserving delivery schedules with available battery capacity.

Predictive waypoint circuits redistribute autonomous vehicles across subregions to improve coverage, reduce latency, and balance demand.

Electrical node data drives dynamic LOTO procedures that cut manual setup time, reduce human error, and avoid unnecessary locks.

Controller-based ESR tracking during state changes estimates energy storage health and supports maintenance before grid disruptions.

Filters restricted curbside segments and ranks legal stop points by distance and availability to improve automated passenger pickup and drop-off.

Autonomous racks, scanning, and real-time feedback reduce manual loading delays, address errors, and item transfer time in delivery.