Interprogram Communication TRIZ Cases

See how a notification control device coordinates sound and image alerts, cancels remaining not

See how adaptive monitoring adjusts reporting frequency based on usage rates and depletion pred

See how threshold-based inventory monitoring and tiered manager alerts enable unmanned coffee s

See how a separate holder with weighing and accelerometer modules distinguishes drinking from p

See how a dispenser reporting system adjusts monitoring frequency based on usage data to reduce

Feedback-based traffic throttling and address remapping ease FPGA NoC congestion, improving throughput and power efficiency.

A hypervisor-based manager shares camera, touch, sensor, audio, and position data across vehicle display VMs with different operating systems.

An intermediary controller turns automation descriptions into endpoint commands, enabling vehicle function updates without direct access risks.

A hypervisor-based camera manager shares camera, sensor, audio, and touch data across vehicle display VMs with less signal-processing complexity.

Shared memory lets vehicle display VMs on different OSs exchange Ethernet and CAN data quickly for synchronized multi-screen image processing.

Multiple diverse packet pipelines and a safety voting module improve in-vehicle switch reliability and reduce common-cause failures.

A supervisory module checks communication function sequences against formal models, helping mixed-criticality software interoperate safely.

Shared memory on a hypervisor lets multiple vehicle displays show identical images in sync while maintaining high-speed communication across different OSs.

A cloud-mediated controller translates automation requests into vehicle actions, expanding function access while reducing update risk and cost.

A detachable radial stall coupling enables full-angle braking in motor tests while reducing alignment effort, calibration time, and inertia.

Shared-memory RPC between vehicle display virtual machines cuts processor load and response delay, including during boot before network activation.

A library bridging layer links applications across different operating systems in vehicles while preserving compatibility, stability, and performance.

A neural network selects equalization profiles by media variant to adapt sound across genre, era, and mood without manual retuning.

Virtual synchrony and replicated server groups keep autonomous vehicle computing consistent and resilient despite higher processing demands.

Virtual machines and a hypervisor let multiple vehicle displays share processing loads and image data across separate signal processors.

A neural network matches equalization profiles to media variants and audio traits, reducing manual tuning while keeping playback consistent.

A single vehicle OS API configures Ethernet interfaces and ACL-based access, reducing low-level setup errors and improving security.

A software middleware layer replaces hardware-heavy ECUs to manage autonomy messages, improving vehicle security, fault tolerance, and reliability.

A layered BEOS with virtual file system support improves in-vehicle code maintainability, portability, and debugging without sacrificing stability.

Standardized and semanticized vehicle control data lets new applications connect without updating the core control program.

Inverted logic-on-logic die stacking improves AI package heat removal and I/O bandwidth while lowering power with ferroelectric logic.

Subtle steering inputs at a vehicle stop reveal road friction from tire response data, improving control without noticeable passenger disruption.

An SDK-based vehicle open platform hides control protocols behind APIs, enabling secure third-party component control without protocol exposure.

A single neural model adapts EQ by media variant, genre, and engineer preference to smooth audio changes with lower processing load.

Inverted logic-on-logic stacking puts compute dies above memory to improve heat removal, bandwidth, and power use in AI packages.

A memory-partitioned enablement framework lets flow RTU applications update independently, cutting full re-release and regression testing burden.

Precomputed command predictions let a client keep real-time control despite TCP/IP latency variation while reducing local compute load.

A platform abstraction layer and shim let IoT-responsive signage content run across mixed hardware and operating systems with less downtime.

Edge and cloud task splitting cuts latency and cloud burden while enabling seamless data exchange between intranet plant systems and external servers.

Independent application containers embed guest OS dependencies once, enabling portable automation control deployment across host operating systems.

A platform abstraction layer lets IoT-triggered signage content run across diverse media players with simpler updates and deployment.

A multi-core UAV controller shares flight data across cores so autopilot, navigation, and AI tasks run without extra hardware, weight, or power.

Parallel avatar and robotic virtual users offload complex data manipulation to AI, cutting user wait time and device storage demand.

Preconfigured web frame restrictions and source whitelists let process plant HMIs be updated in real time without disrupting display execution.

A unified neural network combines dynamic clustering with next-event type and time prediction to track evolving user behavior.

Portable flow and validation sensors capture urine flow rate and volume at home, reducing diary errors and incomplete void records.

A platform abstraction layer and scriptlets let one CMS manage diverse signage players, enable IoT-triggered content, and simplify deployment.

External utility API calls trigger IT-to-OT command mapping so industrial control networks can cut device power use during monitored time windows.

A handheld float-and-magnet uroflowmeter replaces bulky clinic units and handwritten diaries with portable, automatic urine flow measurement and data capture.

Magnetic float sensing in a handheld uroflowmeter enables automatic home capture of urine flow, volume, and duration with less manual logging.

Connector modules standardize sample and process data between production and lab systems, cutting delays and manual errors in chemical control.

A broker-and-adapter gateway lets industrial applications access data across changing storage protocols without direct source-specific updates.

A control-independent data model and generated API simplify food plant process data access, cutting setup time, cost, and scripting errors.

Separating network-based job setup from local programmable-logic execution enables synchronous component control without network delay.

HTML5 message handshakes and bootloader-loaded code files let container and component apps exchange logic across domains without cross-origin violations.

A unidirectional data diode and native data typing expose authorized process plant data to external systems without opening reverse access.

Periodic communication slots split machine data into smaller portions to guarantee transfer time and improve transmission efficiency.

Automated cycling and cross-sensor observation reveal hidden IoT equipment relationships without PLC access, speeding digital twin creation.

Continuous voltage learning generates digital signatures that flag asset degradation early, reducing reactive downtime and maintenance cost.

An adjustable nozzle and sensor bench simulates urine flow at varied angles to validate handheld uroflowmeters for accurate rate, duration, and volume measurement.

Layered identity diffusion and access mediation handle multiple entity perspectives while securely constraining system actions.

Mediated covenants and informatic convolution build event-specific trust models that constrain computing actions while handling alternative viewpoints.

Altering operation-layer structure, order, and redundancy helps protect edge AI models from reverse engineering without losing accuracy.