Data Processing Applications TRIZ Cases

Identifies which new energy terminal or AC bus overvoltage dominates after fault clearing by comparing voltage limits and PLL-linked dynamics.

Historical seasonal load data pre-trains ESS control, then splits schedules into weekdays and holidays to cut peak load without delay.

Surrounding-person detection lets an autonomous taxi adjust speed toward likely riders, raising occupancy and cutting empty-trip energy use.

Server-managed coupling and uncoupling lets autonomous vehicles transfer users between different routes while preserving platooning efficiency.

Inter-vehicle communication adjusts each car’s speed from real-time position data to keep safe spacing in automated valet parking.

A graph neural network predicts actor goals, interactions, and trajectories from state and lane data to improve autonomous motion planning.

Battery data is used to estimate actual EV operation and generate timely reports that improve vehicle usage and maintenance decisions.

Blockchain-based peer inspection lets nearby vehicles verify sensor faults in real time, cutting downtime and improving autonomous driving safety.

Voltage stability indexes across load nodes reveal where a thyristor controlled phase shifter should be installed to reduce collapse risk.

An SVM-based heating-section equivalence model improves electro-thermal virtual power plant aggregation accuracy despite uncertain parameters.

Exterior-access compartments replace central aisles and exit doors, improving package access, storage capacity, and vehicle-independent loading.

Daisy-chain TCP/IP or UDP links between battery management systems cut rack data delays and support larger energy storage capacity.

Autonomous IP packets add priority, routing, and security to support real-time grid data exchange and electricity settlement.

Cost models and optimization algorithms assign spaces for manned and unmanned vehicles to ease congestion and reduce collision risk.

A hierarchical optimizer balances sources, subplants, sinks, and storage to cut central plant energy costs under real-time constraints.

Retrieves similar driving scenarios, filters them by selection conditions, and converts them into realistic ODD-compliant tests for autonomous vehicles.

Balance control runs only when grid support benefits exceed storage deterioration cost, improving power management efficiency.

Bio-signal analysis and metaverse preference data let a vehicle tailor lamps, fragrance, and audio for personalized stress relief.

Automatic interlocks use work terminal position and progress data to block OHT entry into active inspection sections and prevent operator accidents.

Display lamps linked to driver assignment and use state let users quickly identify whether a remote driving taxi is available.

Fleet cruising distance triggers proactive vehicle refueling or charging, preserving dispatch availability and reducing user wait time.

Magnetic couplers let autonomous transit pods stack onto carriers, boosting urban transport throughput while limiting infrastructure expansion.

Sensor fusion and confidence scoring detect vehicle damage, trigger safe relocation, and send targeted alerts to operators or authorities.

PLC signal attenuation helps DER systems identify peers behind the same transformer, enabling local energy sharing and easing grid bottlenecks.

Real-time 3D map monitoring and server-calculated trajectories guide autonomous vehicles to the right parking space while reducing congestion.

Mobile image processing identifies relay panel light signals and overlays guidance, helping users interpret complex interfaces in poor or remote conditions.

Prioritizes vehicle, environment, and driver data by active service needs so critical information reaches the server during communication disruption.

Sensor data identifies crew improvement needs and routes caution alerts in real time, reducing instructor workload across multiple trainees.

Operating signals from loads and smart connectors reveal supply network topology without complex synchronized measurements or production disruption.

A dual passive-active label can be remotely reconfigured to disable resonant identification, avoiding replacement during livestock system updates.

Blockchain-based V2G trading separates renewable and exhaustible electricity to prioritize low-CO2 use and support accurate emissions accounting.

Perception data and ML help autonomous vehicles detect pickup queues, decide when to join, and reduce congestion for other road users.

Randomized energy packet requests let DERs balance grid reserves with consumer QoS while reducing reliance on fast-ramping generators.

By identifying vehicle type and use, the system stores only key battery degradation data to cut storage, transmission, and calculation time.

A shared-memory coprocessor offloads FFT harmonic processing from the meter core, improving real-time analysis while lowering hardware cost.

A correction coefficient aligns scheduled battery power with real-time feedback to stop microgrid backflow and avoid control conflicts.

Historical power data clustering selects PQM deployment points that improve monitoring coverage while avoiding unnecessary device cost.

Harmonic-based load signatures let a smart plug identify appliance operating cycles and send status to home networks without appliance changes.

A transition-matrix dispatch scheme shifts generator cost integration to distributed nodes, easing congestion and avoiding central-node failures.

Rolling spatio-temporal scheduling guides MES vehicle routing and charge-discharge control to cut load loss and support reliable distribution grids.

Pre-authorized user terminal identification simplifies secure remote vehicle access while supporting flexible shared operation conditions.

Gas station communication plus camera and sensor feedback enables precise autonomous driving and fueling with safe manual-mode transition.

Behavioral models trained from SCL files and traffic data detect anomalous utility network behavior, including zero-day malware.

Region- and login-triggered operator workflows automate compliance task assignment and evidence submission across changing local regulations.

Balances planned instrument operation with actual market prices to improve microgrid power trading efficiency and lower transaction costs.

A two-stage controller combines forecast scheduling with on-line dispatch to cut hybrid power optimization complexity and operating cost.

Power meter data reveals IoT cyber, physical, hardware, and software anomalies, enabling fast root cause diagnosis from energy profiles.

Calculates facility electricity charges by reducing total energy use with coefficients tied to specified device groups and operating states.

Current and voltage harmonic analysis lets a smart plug identify appliance loads and operating cycles for home network services.

Category-based alerts use edge-analyzed position history to distinguish students from other pedestrians and warn vehicle occupants earlier at night.