Portable digital court scoring and monitoring device for tennis courts

Abstract

The present invention relates to an integrated portable digital court monitoring and scoring device (10) for tennis courts (17) digitizing tennis experience. The device (10) integrates a variety of different digital services and functions such as electronic scoring (25), court surface condition monitoring (32) with ultrasonic sensors (34), sensor-based moisture detection (38) using infrared (40), ultraviolet (42), and / or temperature (50) sensors. Furthermore, a presence of players (46) can be detected, and a court usage intensity (56) is measured using a variety of electronic sensors such as vibration (58) and / or audio sensors (60). The proposed device supports electronic processes for tennis tournament management (20), court booking (22), and court maintenance (29), digitizing tennis sports experience for players, spectators, club managers, and tournament managers.

Description

[0001] ZP11094WO - MyScore

[0002] 1

[0003] Description

[0004] PORTABLE DIGITAL COURT SCORING AND MONITORING DEVICE FOR TENNIS COURTS

[0005] FIELD OF THE INVENTION

[0006] The present invention relates to an apparatus for tennis courts. More specifically, the invention relates to an integrated portable digital court monitoring and scoring device for tennis courts with advanced sensor fusion technology and real-time data processing capabilities.

[0007] BACKGROUND OF THE INVENTION

[0008] Tennis club managers and tournament organizers face significant operational challenges when managing traditional non-digital tennis courts equipped with basic configurations comprising clay, grass or hard-court surfaces, manual scoreboards, and conventional facility infrastructure. According to established practice, these facilities require extensive manual intervention for court condition assessment, match supervision, and facility utilization tracking.

[0009] Current challenges for club managers include subjective court maintenance scheduling based on visual inspection or predefined schedules, leading to either premature maintenance costs or delayed interventions resulting in surface deterioration and player safety concerns. Tournament organizers encounter difficulties in objective court usage optimization and player-to-court assignments, real-time match monitoring, and accurate scoring verification during competitive events. Manual scoring processes require dedicated personnel for each court, increasing operational costs and introducing human error potential in official match records.

[0010] Existing digital tennis solutions address isolated technical problems through specialized applications including racket-mounted sensors for swing analysis, or ball tracking systems for professional broadcast enhancement. For example, WO2024220368A1 discloses a solutionZP11094WO - MyScore

[0011] 2

[0012] that generates predictive overlays over a video of a tennis match indicating a current state of a match and a likelihood of a ball being returned to various regions of a court. Other disclosures, for example, WO2024044618A1 relate to live tournament prediction based on information associated with the current tournament and player rankings. According to prior art, each solution operates independently without integration, requiring multiple separate systems and failing to provide comprehensive facility management solutions for tennis operators. Current solutions often require permanent court modifications, substantial infrastructure investments, and are economically impractical for club facilities and smaller tournament venues.

[0013] The technical field lacks affordable, portable digital solutions addressing the comprehensive operational requirements of tennis facilities and booking management. The tennis industry demonstrates urgent need for integrated digital solutions that digitize the complete tennis experience, transforming traditional courts into intelligent facilities while maintaining compatibility with existing tennis infrastructure and operational procedures.

[0014] DESCRIPTION OF THE INVENTION

[0015] It is therefore the object of the present invention to provide improved digital systems for supporting the complex requirements for tennis court management and tennis tournament management. The object is solved by the proposed integrated device according to the independent claims. The dependent claims describe particularly useful embodiments of the invention.

[0016] According to the invention, an integrated portable digital court monitoring and scoring device for tennis courts is disclosed. The term "integrated portable digital court monitoring and scoring device" refers to a unified electronic system combining multiple sensing, processing, communications, and display functions within a single transportable unit. This integration distinguishes the invention from prior art solutions comprising separate devices for individual court management functions. The portable configuration enables temporary deployment at various tennis venues without requiring permanent court modifications or extensive infrastructure installation. According to an example, the device integrates multiple functions within a unified housing weighing less than 10 kg for manual transportation. The device comprises a housing configured to be positioned at a tennis court. A housing can be definedZP11094WO - MyScore

[0017] 3

[0018] as a protective enclosure containing and supporting all electronic components, sensors, and mechanical elements of the device.

[0019] The device comprises a processing unit for processing sensor data. The term "processing unit" can refer to computational hardware configured for real-time acquisition, analysis, and control of multiple sensor data streams simultaneously. This component can comprise microprocessor or microcontroller systems, digital signal processors, or system-on-chip implementations optimized for sports facility monitoring applications. According to an example, the processing unit is arranged at a remote server location receiving sensor signals via the communications interface. This allows for centralized provisioning of intelligent functions wherein the device and units on the court are kept simple and robust.

[0020] Sensor data can be defined as digitized measurements and signals generated by various sensing elements monitoring court conditions and player activities. This can encompass analog and digital signals from, for example, ultrasonic, or laser distance sensors, audio pattern recognition systems, infrared moisture detectors, thermal imaging sensors, magnetic angle sensors, and vibration monitoring devices. According to the invention, sensor data refer to sampling rates from 1 Hz to 10 kHz per sensor channel with sufficient precision for tennis facility management applications. Data characteristics can include measurement accuracy specifications, environmental compensation requirements, and temporal correlation analysis for comprehensive court assessment functionality.

[0021] The device comprises a data communications interface configured to connect the device to remote data processing and / or Al analytics, and data storage systems, and a display unit for presenting score values and / or information for players and / or spectators. Furthermore, the device comprises a scoring unit with a plurality of score plates with magnetic angle sensors, wherein each score plate being mechanically rotatable to indicate score values. The processing unit is configured to determine current score values based on angular position signals from the magnetic angle sensors and convert the angular position signals into corresponding score values.

[0022] The term “remote data processing and data storage systems” can refer to external computing infrastructure or backend systems accessible via network communications. These systems can comprise cloud-based servers, tournament management platforms, court bookingZP11094WO - MyScore

[0023] 4

[0024] databases, and maintenance scheduling applications located physically separate from the tennis court device. Examples include AWS / Azure cloud services, tennis facility management software, and tournament organizing platforms requiring real-time court condition data.

[0025] Embodiments can include edge computing nodes for reduced latency processing, distributed database systems for redundant data storage, and hybrid cloud-premises architectures accommodating different facility requirements and regulatory compliance standards across EPC contracting states.

[0026] A display unit can be a visual presentation subsystem configured for information display to users, players, and spectators. The term “score values” refer to numerical or symbolic representations of tennis match progression. A scoring unit can be an electromechanical subsystem integrating manual score adjustment with electronic detection capabilities. The scoring unit can comprise mechanically operated score plates combined with magnetic sensing technology enabling precise electronic tracking of manually set tennis scores.

[0027] A magnetic angle sensor can be a precision electronic component detecting magnetic field orientation changes. Signal conditioning circuits provide digital output interfaces compatible with microprocessor systems. The device comprises a court surface topology sensor assembly comprising an ultrasonic sensor configured to emit high-frequency sound waves for detecting surface height variations, wherein the processing unit is configured for generating court surface topology data. A court surface topology sensor assembly can be a coordinated system of sensing devices configured for three-dimensional surface geometry measurement and analysis. Court surface topology data can be comprehensive three-dimensional geometric information representing elevation characteristics across tennis court areas in digital format.

[0028] The device comprises a moisture sensor assembly comprising an infrared sensor, ultraviolet radiation sensor, and / or ambient temperature sensor, each configured to determine a court surface moisture level. A moisture sensor assembly can be a coordinated multi-sensor system for detecting water content in surfaces. The device comprises a player presence sensor assembly comprising an acoustic, thermal, ultrasonic, visual and / or acceleration sensor configured for detecting a presence of a player on the court. A player presence sensor assembly can be a multi-modal detection system combining multiple sensing technologies for human presence identification within tennis court boundaries.ZP11094WO - MyScore

[0029] 5

[0030] An acoustic sensor can be a microphone or audio transducer configured for detection of human-generated sound patterns within tennis court environments. This can be, for example, a racquet hitting the ball, ball bouncing, a player sliding, and others. A thermal sensor can be an infrared radiation detector configured for identification of human body heat signatures distinguishable from ambient court surface temperatures. An ultrasonic sensor can be an acoustic transducer operating above human hearing range configured for motion detection through Doppler frequency analysis of reflected sound waves. According to an example, a motion detection for player presence is based on laser sensors. A visual sensor can be a digital camera or optical detection device configured for computer vision-based player identification and tracking within tennis court boundaries. An acceleration sensor can be a vibration detector or seismic transducer configured for detection of ground-transmitted mechanical vibrations generated by player movements on court surfaces.

[0031] The device comprises a court usage intensity sensor assembly comprising a vibration sensor and / or an audio sensor, wherein the processing unit is configured to derive a usage intensity factor from the vibration and / or audio sensor signals based on machine learning classification. A court usage intensity sensor assembly can be a multi-sensor system measuring tennis court activity levels through physical parameter detection. Machine learning classification can be algorithmic pattern recognition enabling automated categorization of sensor data into predefined activity classes. According to an embodiment, the magnetic angle sensors are GMR (Giant magnetoresistance) magnetic angle sensors associated with each score plate. A GMR magnetic angle sensor can be a magnetoresistive device detecting magnetic field orientation changes through electrical resistance variations.

[0032] According to an embodiment, the processing unit is configured to extract gameplay-related audio features from the acoustic sensor signals based on a trained machine learning model. The term gameplay-related audio features can refer to characteristic acoustic signatures extracted from tennis match sounds for automated activity and / or presence recognition. According to an example, gameplay-related audio features can comprise ball impact frequencies (200-2000 Hz), footstep patterns (5-200 Hz), racket swing acoustics (100-1000 Hz), and player vocal patterns enabling classification of tennis activities including serving, volleying, baseline rallies, and training exercises through spectral analysis and temporal pattern recognition. According to an example, audio features can alternatively includeZP11094WO - MyScore

[0033] 6

[0034] environmental sounds, equipment noise, and spectator activity requiring filtering algorithms to isolate tennis-specific acoustic signatures from background noise sources for accurate court usage intensity assessment and player presence detection applications.

[0035] A trained machine learning model can be a computational algorithm optimized through supervised learning for automated pattern recognition and classification tasks. According to an example, trained models can comprise neural networks, support vector machines, or decision trees configured for tennis audio classification, achieving accuracy levels exceeding 90% for distinguishing between recreational play, competitive matches, and training activities through preprocessing of acoustic sensor data and feature extraction algorithms. According to an example, machine learning models can alternatively utilize unsupervised learning, reinforcement learning, or hybrid approaches enabling adaptation to specific court environments, player populations, and acoustic conditions without requiring extensive manual training data collection for diverse tennis facility applications.

[0036] According to an embodiment, the processing unit is configured to process weather data received from the data communications interface, for example, via an API, and process sensor data from the different sensor assemblies to predict a future surface topology, surface moisture level for generating maintenance scheduling recommendations. According to an embodiment of the invention, the processing unit is configured to generate, based on acquired sensor data, control data for controlling court maintenance robots. The processing unit can implement autonomous maintenance control algorithms that convert sensor-derived court condition assessments into specific robotic control commands.

[0037] According to an embodiment, the infrared sensors of the moisture sensor assembly are configured to use dual wavelength infrared signals at wavelengths optimized for water molecule absorption characteristics. An infrared sensor can be a photodetector configured for electromagnetic radiation detection in wavelength ranges between 700 nanometers and 1 millimeter. The term infrared sensor can refer to semiconductor devices utilizing photodiodes, phototransistors, or thermopile arrays for converting infrared radiation into electrical signals. According to an example, infrared sensors can comprise near-infrared photodiodes operating at 1450nm wavelength for water absorption spectroscopy, or thermal infrared detectors operating at 8-14pm for temperature measurement applications.ZP11094WO - MyScore

[0038] 7

[0039] Dual wavelength infrared signals can be electromagnetic radiation transmitted at two distinct infrared wavelengths for differential measurement applications. The term dual wavelength infrared signals can refer to spectroscopic techniques utilizing reference and measurement wavelengths for compensation of interference factors. According to an example, dual wavelength infrared signals can comprise 1450nm primary wavelength for water absorption measurement and 1300nm reference wavelength for baseline compensation in outdoor moisture sensing applications.

[0040] Wavelengths optimized for water molecule absorption characteristics can be specific infrared frequencies corresponding to water molecular vibration resonances. The term can refer to near-infrared wavelengths where water molecules exhibit maximum absorption coefficients for enhanced measurement sensitivity. According to an example, wavelengths optimized for water molecule absorption can comprise 1450nm corresponding to first overtone O-H stretching vibrations, or 1940nm wavelengths for combination band water absorption in spectroscopic moisture measurement systems.

[0041] According to an embodiment, the temperature sensors of the moisture sensor assembly are configured to detect heat signatures of objects on the court surface and / or measure temperature differences between the court surface and ambient air. Objects on the court surface can be foreign materials, debris, equipment, or anomalies disrupting normal court conditions. Temperature sensors can be thermistors, RTDs, thermocouples, or infrared photodetectors measuring thermal radiation. According to an example, temperature sensors can comprise non-contact infrared thermometers operating in 8-14 pm wavelength ranges for surface temperature measurement, or contact-based platinum RTD sensors with ±0.1 °C accuracy for ambient air monitoring. The sensors can utilize different measurement principles including resistance change, voltage generation, or infrared radiation detection depending on application requirements.

[0042] According to an example, temperature sensors can be configured as single-point detectors, linear arrays, or two-dimensional thermal imaging systems enabling different spatial resolution requirements. The sensors can operate across temperature ranges from -40°C to +125°C with response times varying from milliseconds for infrared sensors to seconds for thermal mass sensors. Heat signatures can be thermal radiation patterns or temperature distributions indicating object presence and characteristics. According to an example, heatZP11094WO - MyScore

[0043] 8

[0044] signatures can comprise infrared emission patterns from stones, debris, or equipment showing temperature contrasts exceeding 2-10°C relative to court surface background. The signatures can be detected through thermal imaging sensors, infrared thermometers, or thermopile arrays enabling object identification through thermal characteristics rather than visual appearance. Non-contact identification capability enables detection without physical court surface disturbance during ongoing tennis activities. Real-time safety assessment enables immediate identification of hazardous objects requiring urgent removal before player injury occurs.

[0045] According to an embodiment, the data communications interface is configured for transmitting the score values and / or court condition data to external tournament management systems, booking platforms, and / or backend services. According to an embodiment, the device comprises a solar power supply unit with portable solar modules which are configured to be arranged at surroundings of a tennis court. A solar power supply unit can be a photovoltaic energy conversion system providing electrical power through solar radiation. According to an example, the solar modules and / or the power supply unit are arranged in or at the housing. According to an embodiment, the scoring unit is configured to receive data from sensors arranged at a player and / or tennis racket. The term arranged at a player can refer to sensor positioning on human body locations during tennis activities.

[0046] According to an embodiment, the device further comprises a defibrillator unit. A defibrillator unit can be a medical device configured to deliver controlled electrical impulses for cardiac rhythm restoration. The term defibrillator unit can refer to automated external defibrillators (AED), semi-automated defibrillators, or manual defibrillators incorporating rhythm analysis and shock delivery capabilities. According to an example, the device comprises an emergency button enabling the defibrillator. Advantages can be seen in an increased safety of tennis courts during use.

[0047] According to an embodiment, the processing unit is configured to detect markers on the tennis court for calibrating sensors of the different sensor assemblies, wherein markers can be detected based on image analysis, reflections of audio signals, ultrasonic signals, or electromagnetic signals, or runtime of signals. The term markers can refer to reference objects or patterns positioned on court surfaces for sensor calibration purposes. Markers can simplify the calibration process ensuring accuracy of sensor calibration.ZP11094WO - MyScore

[0048] 9

[0049] According to an embodiment, the processing unit is configured to generate, based on sensor data, augmented reality data for controlling an augmented reality display. Augmented reality data can be processed digital information configured for overlaying virtual elements onto real-world visual environments. According to an embodiment, the scoring unit comprises a speech recognition unit with a digital signal processor for recognizing a player’s speech, wherein the speech recognition unit is configured to extract score values from a player’s voice signals. According to an example, the speech recognition unit is configured for classifying identity based on captured player’s voice. This way, information collected can be assigned to a specific person, court, and / or player. According to an example, speech recognition units can utilize hidden Markov models, neural networks, or deep learning algorithms for acoustic pattern analysis. Speech recognition units can operate in real-time or batch processing modes, supporting continuous speech recognition or isolated word recognition depending on tennis scoring requirements.

[0050] A digital signal processor can be a specialized microprocessor optimized for mathematical operations on digitized signals. The term digital signal processor can refer to dedicated DSP chips, ARM Cortex-M series processors, or FPGA implementations with signal processing capabilities. According to an example, digital signal processors can execute fast Fourier transforms, filtering operations, and pattern recognition algorithms at sampling rates exceeding 48 kHz. Digital signal processors can provide hardware acceleration for speech recognition algorithms, enabling real-time voice processing with latency below 100 milliseconds suitable for tennis scoring applications.

[0051] Extracting score values can be a computational process for identifying tennis scoring terms from processed speech data. The term extract score values can refer to pattern matching algorithms that correlate recognized words with predefined tennis scoring vocabulary.

[0052] According to an example, extract score values can identify terms including "fifteen," "thirty," "forty," "deuce," "advantage," and "game" from continuous speech streams. Extract score values can utilize context-aware processing considering tennis scoring rules and match progression to validate extracted scoring information and reject spurious recognition results. The combination of speech recognition unit with digital signal processor enables automated tennis scoring through voice command processing, eliminating manual score adjustment requirements while providing real-time match documentation capabilities.ZP11094WO - MyScore

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[0054] BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The advantages of the invention will now be illustrated in more detail with reference to embodiments and figures showing:

[0056] Fig. 1 shows an integrated portable digital court monitoring and scoring device for tennis courts according to the invention.

[0057] Fig. 2 shows a court surface topology sensor assembly according to the invention arranged at a tennis court.

[0058] Fig. 3 shows a moisture sensor assembly with different sensors according to the invention.

[0059] Fig. 4 shows a player’s presence sensor assembly with different sensors according to the invention.

[0060] Fig. 5 shows a court usage intensity sensor assembly with a vibration sensor and audio sensor according to the invention.

[0061] Fig. 6 shows the portable digital court monitoring and scoring device connected to remote tournament management and booking platforms.

[0062] Fig. 7 shows a scoring and monitoring device with a solar power supply unit and portable solar modules according to the invention.

[0063] Fig. 8 shows a processing unit of the scoring and monitoring device configured to control an augmented reality display.

[0064] Fig. 9 shows a device according to the invention with a scoring unit configured for receiving data from a tennis racket sensor.ZP11094WO - MyScore

[0065] 11

[0066] The reference symbols used in the drawings, and their meanings, are listed in summary form in the list of reference signs. In principle, identical parts are provided with the same reference symbols in the figures.

[0067] DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

[0068] Fig. 1 discloses a scoring and monitoring device 10 for tennis courts 17. A housing 11 provides environmental protection meeting IP65 ingress protection standards, ensuring reliable operation under outdoor tennis court 17 conditions including temperature variations, humidity exposure, and mechanical impacts. According to various embodiments, the housing 11 comprises weather-resistant materials such as impact-resistant polycarbonate or aluminum alloy construction with corrosion-resistant surface treatments suitable for extended outdoor deployment. Dimensional specifications can typically range from 300-1000 mm height, 400-1000mm width, and 10-150mm depth, providing sufficient internal volume for component integration while maintaining portability requirements. According to another example, the device can be implemented in a larger housing, for example, integrated in a surrounding court edging or court display unit.

[0069] A processing unit 12 provides sufficient computational capacity for machine learning inference, sensor fusion algorithms, and real-time communication protocols without requiring external computing resources during normal operation. In an example, technical specifications include a multi-core ARM or x86 processor or microcontroller architecture operating at frequencies exceeding 1 GHz, volatile memory capacity ranging from 2-8 GB, and analog-to-digital conversion capabilities supporting 12-24 bit resolution across multiple simultaneous channels. Examples include embedded Linux or real-time operating system implementations enabling deterministic response times for critical scoring applications, and edge computing capabilities supporting local artificial intelligence processing for player detection and court condition analysis.

[0070] A data communications interface 14 can be a hardware / software subsystem enabling bidirectional data exchange with external systems. The interface 14 can comprise wireless communication protocols including Wi-Fi IEEE 802.11ac / ax standards, Bluetooth Low Energy 5.0+, and cellular connectivity supporting 4G LTE / 5G networks for remote connectivity. Wired communication options can include Ethernet 10 / 100 / 1000 Mbps, USB 3.0+ interfaces, andZP11094WO - MyScore

[0071] 12

[0072] serial protocols RS-232 / RS-485 for legacy system integration. According to further examples, the interface 14 can encompass mesh networking capabilities for multi-device coordination, security implementations including WPA3 encryption and TLS 1.3 protocols, and data compression algorithms enabling efficient transmission under varying network conditions across different technical environments.

[0073] A display unit 24 can comprise LCD, LED, OLED, or electronic paper display technologies with brightness specifications exceeding 1000 cd / m2for outdoor visibility. Dimensional ranges can be from 10-24 inches diagonal with touch-screen functionality, automatic brightness adjustment, and viewing angles exceeding 160° horizontally / vertically. Character heights can comply with tennis facility standards (100-300mm) ensuring visibility from standard spectator distances under varying lighting conditions. Score values 26 represent numerical or symbolical tennis match progressions. Score values 26 comprise game scores (0, 15, 30, 40, deuce, advantage), set scores (numerical counts), tiebreak points (0-20+), and match indicators following official tennis scoring conventions established by International Tennis Federation (ITF). Examples include "6-4, 3-2" indicating set and game progression. Embodiments can accommodate different tennis formats including singles, doubles, pro-set scoring, and tournament-specific modifications.

[0074] Score plates 28 can refer to mechanically rotatable discs or cylinders displaying individual score elements. Score plates 28 can comprise aluminum or high-strength polymer construction with diameters 100-300mm, incorporating embedded permanent magnets creating distinct magnetic field orientations corresponding to angular positions. Each plate 28 can represent specific scoring elements: games, sets, tiebreak points, or match indicators. According to an example, different magnetic configurations including neodymium permanent magnets, multiple magnetic poles for enhanced position resolution, and weather-resistant magnetic materials are applied maintaining performance across temperature variations. Alternative embodiments can utilize ferromagnetic targets or electromagnetic actuation systems.

[0075] A magnetic angle sensor 30 can include multi-pole magnetic encoding for enhanced resolution, temperature compensation circuits for outdoor applications, and redundant sensor configurations for fault tolerance. Alternative embodiments can utilize optical encoders, potentiometric sensors, or capacitive angle detection depending on environmentalZP11094WO - MyScore

[0076] 13

[0077] requirements and precision specifications. The term "angular position signals" can refer to electrical outputs from magnetic angle sensors indicating rotational orientation of score plates 28. According to an example, GMR sensors can comprise multiple ferromagnetic layers with antiferromagnetic coupling, achieving angular resolution below 0.1° across temperature ranges from -40°C to +125°C. The sensors 30 can operate with permanent magnets positioned 1-50mm distance, providing non-contact angular measurement for rotatable score plates 28 in tennis scoring applications.

[0078] According to an example, GMR angle sensors 30 can alternatively comprise anisotropic magnetoresistance (AMR) or tunneling magnetoresistance (TMR) technologies offering different sensitivity characteristics, power consumption levels, and cost considerations for various tennis scoring device implementations requiring angular position detection accuracy. A conversion of angular position signals of the magnetic sensors 30 to score values 26 can be implemented as follows: The processing unit 12 implements analog-to-digital converter (ADC) subsystems to acquire angular position signals from magnetic sensors 30 and converts voltage levels into precise angular measurements (0-360°). Calibration lookup tables store correlation data mapping specific angular positions to tennis score values 26 (example: 0°^"0", 90°^"15", 180°^"30", 270°^"40"), with interpolation algorithms determining positions between reference points.

[0079] A court surface topology sensor assembly 32 comprises an ultrasonic sensor 34 configured to emit high-frequency sound waves for detecting surface height variations, wherein the processing unit 12 is configured for generating court surface topology data 36. A court surface topology sensor assembly 32 can be a coordinated system of sensing devices configured for three-dimensional surface geometry measurement and analysis.

[0080] The device 10 comprises a moisture sensor assembly 38 comprising an infrared sensor 40, ultraviolet radiation sensor 42, and / or ambient temperature sensor 44, each configured to determine a court surface moisture level. A moisture sensor assembly 38 can be a coordinated multi-sensor system for detecting water content in surfaces. A player presence sensor assembly 46 comprises an acoustic 48, thermal 50, ultrasonic 51, visual 52 and / or acceleration sensor 54 configured for detecting a presence of a player on the court. A free-busy indicator 47 can display a booked or non-booked status of a court.ZP11094WO - MyScore

[0081] 14

[0082] A player presence sensor assembly 46 can be a multi-modal detection system combining multiple sensing technologies for human presence identification within tennis court 17 boundaries. The assembly 46 can integrate sensors with overlapping detection zones covering court areas including service boxes, baseline regions, and net vicinity for comprehensive monitoring coverage. According to an example, the sensor assembly 46 can implement sensor fusion algorithms combining detection signals from multiple sensor types to generate confidence-weighted presence indicators, reducing false positive detections from environmental interference, non-human objects, or maintenance personnel moving within court boundaries.

[0083] The term "presence of a player" refers to confirmed detection of human occupancy within designated tennis court 17 boundaries during active or inactive periods. According to an example, presence detection can encompass both active player engagement in tennis activities and passive court occupancy including rest periods, equipment preparation, or court inspection activities, with detection algorithms distinguishing between authorized court users and unauthorized access situations. The presence determination can account for temporary absence periods during normal match play including changeover breaks and equipment retrieval. According to an example, a presence of a player can be qualified through confidence levels indicating detection certainty, with threshold parameters configurable for different application requirements including security monitoring, usage tracking, or automated facility management functions.

[0084] A court usage intensity sensor assembly 56 comprises a vibration sensor 58 and / or an audio sensor 60, wherein the processing unit 12 is configured to derive a usage intensity factor from the vibration 58 and / or audio sensor 60 signals based on machine learning classification. A court usage intensity sensor assembly 56 can be a multi-sensor system measuring tennis court 17 activity levels through physical parameter detection.

[0085] The device further comprises a defibrillator unit 72. A defibrillator unit 72 can be a medical device configured to deliver controlled electrical impulses for cardiac rhythm restoration. According to an example, the defibrillator unit 72 can comprise portable AED devices with voice-guided operation protocols, biphasic waveform generators delivering 150-360 joules, and integrated patient monitoring electrodes. According to another example, the defibrillator unit 72 can include semi-automated devices with manual shock authorization, advancedZP11094WO - MyScore

[0086] 15

[0087] rhythm analysis algorithms, and data logging capabilities for medical record integration. According to an example, the processing unit 12 is configured to send a defibrillator request via the data communications unit 14 to a centralized club defibrillator station including information which court has requested the defibrillator. The integration of a defibrillator unit 72 with the portable tennis court monitoring device provides enhanced emergency medical response capabilities during tennis activities, enabling immediate cardiac intervention without requiring separate emergency equipment deployment.

[0088] In Fig. 2, a court surface topology sensor assembly 32 is disclosed. Depicted is a tennis court 17 with a portable device 10 for court monitoring and scoring arranged next to the tennis net 19. A net sensor 53 is attached to the net to detect ball contacts and is configured to provide a net sensor signal to the processing unit 12. The court surface topology sensor assembly 32 can comprise multiple ultrasonic transducers 34 arranged in arrays, linear configurations, or scanning mechanisms to provide comprehensive court surface coverage. According to an example, the sensor assembly 32 can include environmental compensation sensors such as temperature and humidity detectors for acoustic velocity correction. The assembly 32 can alternatively be implemented as fixed installations, motorized scanning systems, or portable measurement units depending on specific court monitoring requirements. Examples can include multi-element ultrasonic arrays 34 with 4-16 individual transducers, scanning mechanisms providing 360-degree coverage, or distributed sensor networks covering entire court areas.

[0089] An ultrasonic sensor 34 can be a piezoelectric transducer device configured for acoustic wave generation and reception in frequencies above human hearing range. The sensor can operate in frequency ranges from 20 kHz to 2 MHz depending on measurement resolution requirements and environmental conditions. According to an example, ultrasonic sensors 34 can comprise single-element transducers for point measurements, phased arrays for beam steering capabilities, or dual-element configurations separating transmit and receive functions. The sensor 34 can include acoustic matching layers, backing materials, and protective housing for outdoor sports applications.

[0090] Other examples can include air-coupled ultrasonic sensors for non-contact measurements, immersion transducers for wet surface conditions, or contact sensors for enhanced coupling. The sensor 34 can incorporate temperature compensation, beam focusing elements, orZP11094WO - MyScore

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[0092] variable frequency operation for optimized performance across different court surface materials and environmental conditions. Surface height variations can be three-dimensional elevation differences across court surfaces measured relative to reference planes or datum levels. The height variations can range from sub-millimeter irregularities affecting ball bounce characteristics to centimeter-scale depressions requiring maintenance intervention.

[0093] According to measurement principles, height variations can be detected through acoustic time-of-flight analysis, triangulation methods, or interferometric techniques depending on required precision and measurement range. Variations can result from surface wear, settling, thermal expansion, or foreign object deposits.

[0094] According to an embodiment, the device comprises a visual inspection camera 62, wherein the processing unit 12 or the camera 62 is configured to detect surface defects using classification of the camera signals based on a trained machine learning model. A visual inspection camera 62 can be a digital imaging device configured for automated surface monitoring applications. A visual inspection camera 62 can refer to CCD, CMOS, or infrared imaging sensors with resolution ranging from 640x480 to 4K pixels. According to an example, industrial cameras with macro lenses can provide sub-millimeter defect detection capabilities for court surface analysis. According to an example, the visual inspection camera 62 can comprise weatherproof housing with IP65 protection rating, autofocus mechanisms, and LED illumination systems for consistent imaging under varying environmental conditions.

[0095] A trained machine learning model can be algorithms configured through supervised learning using labeled defect datasets for automated recognition. A trained machine learning model can refer to convolutional neural networks, random forests, or ensemble methods optimized for specific defect detection applications. According to an example, models trained on 10,000+ labeled court images can achieve 98% accuracy for common defect classifications.

[0096] The processing unit 12 of the device 10 is configured for generating court surface topology data 36. These data can comprise height maps, contour representations, slope analysis, or volumetric calculations enabling objective surface condition assessment and maintenance planning. Topology data can be stored as point clouds, mesh representations, raster images, or mathematical surface models depending on processing requirements and visualization applications. Data resolution can range from millimeter-scale precision for detailed analysis to centimeter-scale sampling for general monitoring. The topology data can supportZP11094WO - MyScore

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[0098] automated defect detection, predictive maintenance algorithms, or integration with computer-aided design systems for facility planning and renovation projects.

[0099] The processing unit 12 is configured to detect markers 74 on the tennis court 17 for calibrating sensors of the different sensor assemblies, wherein markers 74 can be detected based on image analysis, reflections of audio signals, ultrasonic signals, electromagnetic signals, or runtime of signals. Markers 74 can comprise retroreflective targets, geometric patterns, electromagnetic transponders, or acoustic reflectors with known physical dimensions and positions. Markers 74 can enable automated sensor alignment and measurement accuracy verification through comparison with predetermined reference coordinates. The combination of multiple signal types for marker 74 detection provides redundant calibration capabilities ensuring reliable sensor accuracy across diverse environmental conditions and court surface variations.

[0100] In Fig. 3 a moisture sensor assembly 38 is shown. It comprises an infrared sensor 40, ultraviolet radiation sensor 42, and / or ambient temperature sensor 44, each configured to determine a court surface moisture level. The moisture sensor assembly 38 can comprise multiple sensing technologies operating simultaneously to provide comprehensive moisture detection capabilities through complementary measurement principles. The assembly can include various sensor configurations such as spectroscopic sensors, capacitive sensors, or thermal sensors integrated within a single housing or distributed across measurement areas.

[0101] The coordinated operation enables cross-validation of moisture measurements and compensation for environmental interference factors affecting individual sensor accuracy. According to an example, a moisture sensor assembly 38 can comprise dual-wavelength infrared photodetectors operating at 1450nm and 1300nm wavelengths combined with UV reflection sensors and precision temperature sensors, providing redundant moisture measurement validation through independent physical detection principles for tennis court 17 surface applications.

[0102] An infrared sensor 40 can be a photodetector configured for electromagnetic radiation detection in wavelength ranges above visible light. The infrared sensor 40 operates by detecting electromagnetic radiation in spectral ranges typically between 700nm and 1mm wavelength, encompassing near-infrared, mid-infrared, and far-infrared regions. The sensorZP11094WO - MyScore

[0103] 18

[0104] can comprise photodiodes, phototransistors, thermopiles, or focal plane arrays optimized for specific infrared wavelength bands relevant to moisture detection applications. Signal processing circuitry converts detected infrared radiation into electrical signals proportional to incident radiation intensity or spectral characteristics. According to an example, an infrared sensor 40 for moisture detection can comprise InGaAs photodiodes operating at 1450nm wavelength where water molecules exhibit strong absorption characteristics, enabling quantitative moisture content determination through differential absorption spectroscopy techniques with measurement accuracy within ±2% moisture content.

[0105] An ultraviolet radiation sensor 42 can be a photodetector responsive to electromagnetic radiation below visible light wavelengths. The ultraviolet radiation sensor 42 detects electromagnetic radiation in wavelength ranges typically between 200nm and 400nm, encompassing IIV-A, IIV-B, and IIV-C spectral regions. The sensor 42 can comprise silicon photodiodes with UV-enhanced responsivity, silicon carbide photodetectors, or photomultiplier tubes optimized for ultraviolet detection applications. UV sensors enable surface reflection analysis and optical property assessment for moisture detection through changes in surface reflectance characteristics associated with water presence. According to an example, an ultraviolet radiation sensor 42 can comprise silicon photodiodes with IIV-A responsivity (315-400nm) combined with optical filters for wavelength selectivity, enabling detection of surface moisture through UV reflectance variations with sensitivity levels detecting moisture content changes as low as 1% surface coverage.

[0106] An ambient temperature sensor 44 can be a thermal measurement device for detecting environmental air temperature conditions. The ambient temperature sensor 44 measures thermal conditions in the immediate environment surrounding the moisture sensing system, providing essential calibration data for moisture calculations and environmental compensation algorithms. The sensor 44 can comprise thermistors, resistance temperature detectors (RTD), thermocouples, or integrated circuit temperature sensors with accuracy specifications suitable for precision moisture assessment applications. According to an example, an ambient temperature sensor 44 can comprise platinum RTD elements with accuracy specifications within ±0.1 °C across temperature ranges from -40°C to +85°C, providing precision temperature measurements for infrared sensor 40 calibration and moisture evaporation rate modeling in outdoor tennis court 17 applications.ZP11094WO - MyScore

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[0108] Court surface moisture level can be a quantitative measurement representing water content present on tennis court 17 playing surfaces. The court surface moisture level indicates the amount of water present on or within the upper layers of tennis court 17 surfaces, expressed as percentage moisture content, absolute moisture values, or categorical classifications affecting court playability and safety conditions. According to an example, court surface moisture level can be expressed as percentage values ranging from 0% (completely dry) to 50% (heavily saturated) with corresponding playability classifications such as "Playable" (<10% moisture), "Marginal" (10-20% moisture), and "Unplayable" (>20% moisture) based on established tennis facility safety standards and surface material specifications.

[0109] In Fig. 4 a player presence sensor assembly 46 is shown. It comprises an acoustic 48, thermal 50, ultrasonic 51, visual 52, and / or acceleration sensor 54 configured for detecting a presence of a player on the court 17. According to an example, the acoustic sensor 48 can comprise omnidirectional or directional microphone arrays with frequency response covering human voice ranges, footstep sounds, and breathing patterns, enabling detection through characteristic audio signatures associated with player activities. The sensor 48 can utilize digital signal processing algorithms for pattern recognition distinguishing tennis-related sounds from environmental noise sources. According to an example, the acoustic sensor 48 can implement beamforming technology focusing detection sensitivity toward specific court zones while suppressing acoustic interference from spectator areas, traffic noise, or adjacent court activities through spatial filtering techniques.

[0110] According to an example, the thermal sensor 50 can comprise passive infrared (PIR) detectors with detection ranges covering typical tennis court 17 dimensions, operating through detection of thermal radiation differences between human body temperature and background court surface temperatures. The sensor 50 can achieve detection sensitivity sufficient for identifying stationary or moving players under various weather conditions.

[0111] According to an example, the thermal sensor 50 can utilize focal plane array technology enabling thermal imaging capabilities for precise player positioning and movement tracking, providing spatial resolution sufficient for distinguishing individual players in doubles match configurations.

[0112] According to an example, the ultrasonic sensor 51 can emit high-frequency acoustic pulses and analyze reflected signals for movement detection, providing distance measurementZP11094WO - MyScore

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[0114] capabilities and velocity calculations for moving objects within detection range. The sensor 51 can operate at frequencies above 20 kHz avoiding interference with court activities while maintaining detection accuracy for human-scale movements. According to an example, the ultrasonic sensor 51 can implement multiple transducer configurations enabling detection zone shaping and beam steering for optimized coverage of specific court areas while minimizing false detections from ball movement or equipment displacement.

[0115] According to an example, the visual sensor 52 can comprise high-resolution imaging systems with object recognition algorithms capable of distinguishing human figures from court equipment, surface markings, and environmental objects through machine learning classification techniques. The sensor 52 can provide detailed spatial information including player positions, movement patterns, and activity classification. According to an example, the visual sensor 52 can implement infrared or low-light imaging capabilities enabling player detection under reduced lighting conditions, utilizing image enhancement algorithms and adaptive exposure control for consistent detection performance across varying illumination levels.

[0116] According to an example, the acceleration sensor 54 can comprise piezoelectric or capacitive accelerometers with sensitivity ranges suitable for detecting footstep-generated vibrations transmitted through court surface materials, enabling player presence detection through characteristic vibration patterns associated with human locomotion. The sensor 54 can distinguish between different activity intensities based on acceleration amplitude and frequency characteristics. According to an example, the acceleration sensor 54 can utilize multi-axis detection capabilities enabling analysis of vibration direction and magnitude for enhanced player movement characterization, providing information about player activity levels and movement patterns through ground-coupled vibration analysis.

[0117] Fig. 5 shows a court usage intensity sensor assembly 56 with a vibration sensor 58 and an audio sensor 60. According to an example, the assembly can comprise additional accelerometers detecting ground vibrations from footsteps, microphones capturing gameplay sounds, or strain gauges monitoring surface deformation. The assembly can integrate multiple sensor types including piezoelectric transducers, seismic sensors, or acoustic arrays positioned around court perimeters or embedded within portable housings. According to an example, implementations can include wireless sensor networks distributed across courtZP11094WO - MyScore

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[0119] surfaces, centralized sensor clusters within scoreboard installations, or mobile sensor platforms enabling temporary tournament deployment. The assembly can provide real-time data streams with sampling rates from 100 Hz to 10 kHz depending on activity detection requirements.

[0120] A vibration sensor 58 can be an accelerometer or transducer detecting mechanical oscillations from tennis court 17 activities. According to an example, the sensor 58 can comprise MEMS accelerometers measuring ground-transmitted vibrations from player movements, piezoelectric sensors detecting ball impact forces, or geophone devices monitoring surface displacement. Sensitivity ranges can span 0.001g to 100g acceleration with frequency response covering 1 Hz to 1000 Hz for comprehensive activity detection. According to an example, configurations can include tri-axial accelerometers providing directional movement analysis, single-axis sensors optimized for vertical impact detection, or distributed sensor arrays enabling spatial vibration mapping. Installation methods can comprise surface mounting, subsurface embedding, or portable positioning depending on court infrastructure requirements.

[0121] An audio sensor 60 can be a microphone system capturing acoustic signatures from tennis gameplay and court activities. According to an example, the sensor 60 can comprise omnidirectional microphones detecting ball impacts, slides and footsteps, directional microphone arrays isolating specific court zones, or noise-canceling systems filtering environmental interference. Frequency response can cover 20 Hz to 20 kHz with dynamic ranges exceeding 80 dB for comprehensive sound capture. Signal processing can comprise real-time spectral analysis, pattern recognition algorithms, or acoustic event classification systems.

[0122] A usage intensity factor can be a quantitative metric representing tennis court 17 activity levels derived from sensor data 78 measurements. According to an example, the factor can comprise numerical scores from 0-100 indicating recreational to professional play intensity, weighted coefficients combining multiple sensor inputs, or time-averaged activity measures enabling usage comparison. Calculation methods can incorporate vibration amplitude analysis, acoustic energy integration, or movement frequency assessment. According to an example, applications can include maintenance scheduling optimization based on cumulative intensity scores, court allocation decisions using real-time intensity monitoring, or facilityZP11094WO - MyScore

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[0124] utilization reporting through historical intensity data analysis which can optionally be combined with weather data fetched from a weather database 18 (see Fig 6). Output formats can comprise continuous intensity values, discrete activity classifications, or statistical intensity distributions.

[0125] According to an example, algorithms as part of the machine learning classification method can comprise neural networks training on tennis-specific activity patterns, support vector machines distinguishing between usage intensity levels, or decision trees classifying court activities based on sensor features. Training datasets can include thousands of labeled examples covering diverse playing styles and environmental conditions. According to an example, implementations can include supervised learning requiring labeled training data, unsupervised clustering identifying natural activity groupings, or reinforcement learning optimizing classification performance through operational feedback. Deployment options can comprise embedded inference engines, cloud-based classification services, or hybrid approaches combining local and remote processing capabilities.

[0126] Fig. 6 shows a portable device 10 wherein the data communications interface 14 is configured for transmitting the score values 26 and / or court condition data to external tournament management systems 20, booking platforms 22 and / or backend servers 16. External tournament management systems 20 can be software platforms managing competitive tennis events including player registration, draw generation, scheduling, and results tracking. According to an example, these systems can include commercial platforms such as Tennis Tournament Planner (TTP), Universal Tennis Rating (UTR), or International Tennis Federation (ITF) tournament software. Booking platforms 22 can be software applications enabling court reservation, scheduling, and facility access management for tennis venues and recreational facilities.

[0127] Additionally, the processing unit 12 is configured to process weather data from a weather database 18 to predict a future surface topology, surface moisture level for generating maintenance scheduling recommendations. This generating of maintenance scheduling recommendations is performed in a court maintenance management system 29 which can be accessed via data communications. Weather data can be meteorological information comprising temperature, humidity, precipitation, and atmospheric pressure measurements.ZP11094WO - MyScore

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[0129] According to an example, weather data can include current atmospheric conditions, historical weather patterns, and forecast predictions from meteorological services.

[0130] The weather data can be obtained from local weather stations, internet-based weather services, or integrated meteorological sensors providing real-time environmental measurements. According to an example, weather data can comprise wind speed measurements, solar radiation levels, barometric pressure readings, and precipitation probability forecasts. The weather data processing can enable correlation between atmospheric conditions and court surface degradation patterns for predictive maintenance applications. According to the invention, the prediction methodology can comprise a multistage data processing pipeline integrating heterogeneous data sources through sophisticated fusion algorithms. The processing unit 12 implements data preprocessing procedures including temporal synchronization of sensor measurements, environmental data correlation, and measurement validation through cross-reference analysis between multiple sensor modalities.

[0131] According to an example, maintenance scheduling recommendations comprise multiobjective optimization algorithms balancing court condition requirements, facility usage demands, weather constraints, and maintenance resource availability. The processing unit 12 implements predictive maintenance strategies minimizing total facility lifecycle costs while ensuring safety and performance standards compliance. Condition threshold modeling utilizes predicted surface topology and moisture levels establishing maintenance trigger criteria based on court playability standards, safety requirements, and surface degradation progression rates.

[0132] The processing unit 12 implements risk assessment algorithms evaluating a consequence severity of delayed maintenance interventions versus immediate maintenance costs.

[0133] Resource optimization algorithms comprise scheduling procedures accounting for maintenance crew availability, equipment accessibility, material procurement lead times, and facility usage calendar constraints. The processing unit 12 implements constraint satisfaction algorithms generating feasible maintenance schedules maximizing court availability while ensuring adequate surface condition maintenance.ZP11094WO - MyScore

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[0135] Further in Fig. 6, the processing unit 12 is configured to generate, based on acquired sensor data 78 (see Fig. 8), control data for controlling court maintenance robots. For that purpose, a maintenance robot control unit 76 is provided. The processing unit 12 can implement autonomous maintenance control algorithms that convert sensor-derived court condition assessments into specific robotic control commands. The processing unit 12 analyzes realtime sensor data 78 including surface topology measurements, moisture levels, debris detection, and foreign object identification to generate targeted maintenance instructions for automated court maintenance systems. The processing unit 12 can comprise robotic communication interfaces supporting standard industrial automation protocols including CANbus, Modbus, or proprietary wireless communication systems for maintenance robot coordination.

[0136] In Fig. 7 an implementation example of the monitoring and scoring device 10 comprises a solar power supply unit 64 with portable solar modules 66 configured to be arranged at surroundings of a tennis court 17. According to an example, the solar power supply unit 64 can comprise photovoltaic panels 66, battery storage systems, charge controllers, and power conditioning electronics configured for outdoor sports facility applications. The unit 64 can include maximum power point tracking (MPPT) controllers optimizing energy harvesting efficiency across varying solar irradiation conditions. According to an example, the solar power supply unit 64 can provide DC output voltages ranging from 12V to 48V or AC output through integrated inverters supporting standard electrical equipment requirements. The unit can incorporate weatherproof enclosures rated IP65 or higher, ensuring reliable operation under tennis court 17 environmental conditions including temperature ranges from -20°C to +60°C.

[0137] Portable solar modules 66 can be movable photovoltaic panels configured for temporary installation and repositioning applications. According to an example, portable solar modules 66 can comprise monocrystalline or polycrystalline silicon photovoltaic cells with power ratings ranging from 50Wto 400W per module, incorporating lightweight aluminum frames and tempered glass surfaces suitable for outdoor deployment. The term "surroundings of a tennis court 17" can refer to adjacent areas within proximity to official court boundaries available for equipment placement. According to an example, portable solar modules 66 can feature folding or modular configurations reducing storage volume during transport, with operational deployment areas ranging from 1m2to 4m2per module. The modules canZP11094WO - MyScore

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[0139] incorporate bypass diodes preventing power loss from partial shading conditions and MC4 connectors enabling series or parallel electrical configurations.

[0140] The scoring unit 25 comprises a speech recognition unit 84 with a digital signal processor for recognizing a player’s speech, wherein the speech recognition unit 84 is configured to extract score values 26 from a player’s voice signals. The voice command from a player is received by an audio sensor 60 and processed by the speech recognition unit 84. A speech recognition unit 84 can be an electronic system configured for converting spoken words into digital data. The term speech recognition unit 84 can refer to hardware-software combinations comprising microphones, analog-to-digital converters, and pattern matching algorithms.

[0141] Fig. 8 shows an example of a device 10 with a processing unit 12 which is configured to generate, based on sensor data 78, augmented reality data 80 for controlling an augmented reality display 82. Augmented reality data 80 can be processed digital information configured for overlaying virtual elements onto real-world visual environments. According to an example, augmented reality data 80 can comprise 3D object coordinates, texture mappings, lighting parameters, animation sequences, or interactive user interface elements. The augmented reality data 80 can include spatial tracking information, depth maps, and occlusion detection parameters. According to an example, augmented reality data 80 can incorporate real-time sensor measurements transformed into visual representations such as heat maps, trajectory lines, measurement annotations, or status indicators. The augmented reality data 80 can be formatted as OpenGL rendering commands, Unity3D assets, or standardized AR frameworks (ARCore, ARKit). An augmented reality display 82 can be a visual output device configured for presenting virtual content superimposed onto real-world scenes.

[0142] According to an example, the augmented reality display 82 can comprise head-mounted displays (HMD), smart glasses, tablet computers, smartphones, or projection systems. The augmented reality display 82 can provide resolution from 720p to 4K with refresh rates ranging from 60-120 Hz. According to an example, the augmented reality display 82 can include optical see-through displays, video see-through displays, or spatial augmented reality projectors. The augmented reality display 82 can incorporate eye tracking, gesture recognition, or voice control interfaces for user interaction. The combination of processing unit 12 generating augmented reality data 80 from sensor measurements enables real-timeZP11094WO - MyScore

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[0144] visualization of invisible physical phenomena, enhancing user understanding and decisionmaking capabilities in technical applications.

[0145] In Fig. 9 the scoring unit 25 is configured to receive data from sensors arranged at a tennis racket 68. Sensors arranged at a player can be attached to wrist-worn devices, embedded in clothing or footwear, or integrated into protective equipment such as wristbands or headbands. The arrangement can enable measurement of player biomechanics including arm movement patterns, body acceleration during court movement, or physiological parameters such as heart rate and body temperature.

[0146] While the invention has been illustrated and described in detail in the drawings and foregoing description, such illustration and description are to be considered illustrative or exemplary and not restrictive; the invention is not limited to the disclosed embodiments. Other variations to the disclosed embodiments can be understood and effected by those skilled in the art and practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims. In the claims, the word “comprising” does not exclude other elements or steps, and the indefinite article “a” or “an” does not exclude a plurality. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. Any reference signs in the claims should not be construed as limiting the scope.ZP11094WO - MyScore

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[0148] Reference signs

[0149] 10 scoring and monitoring device for tennis courts 11 housing

[0150] 12 processing unit

[0151] 14 data communications interface

[0152] 16 backend server

[0153] 17 tennis court

[0154] 18 weather database

[0155] 19 tennis net

[0156] 20 tournament management system

[0157] 22 booking platform

[0158] 24 display unit

[0159] 25 scoring unit

[0160] 26 score values

[0161] 28 score plates

[0162] 29 court maintenance management system

[0163] 30 magnetic sensor

[0164] 32 court surface topology sensor assembly

[0165] 34 ultrasonic sensor for surface monitoring

[0166] 36 court surface topology data

[0167] 38 moisture sensor assembly

[0168] 40 infrared sensor

[0169] 42 ultraviolet radiation sensor

[0170] 44 ambient temperature sensor

[0171] 46 player presence sensor assembly

[0172] 47 free-busy indicator

[0173] 48 acoustic sensor

[0174] 50 thermal sensor

[0175] 51 ultrasonic sensor for player presence

[0176] 52 visual sensor

[0177] 53 net sensor

[0178] 54 acceleration sensor

[0179] 56 court usage intensity sensor assemblyZP11094WO - MyScore

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[0181] 58 vibration sensor

[0182] 60 audio sensor

[0183] 62 visual inspection camera for detection of surface defects 64 power supply unit

[0184] 66 solar modules

[0185] 68 tennis racket

[0186] 70 racket sensor unit

[0187] 72 defibrillator unit

[0188] 74 marker for calibration

[0189] 76 Maintenance robot control unit

[0190] 78 sensor data (various)

[0191] 80 augmented reality data

[0192] 82 augmented reality display

[0193] 84 speech recognition unit

Claims

ZP11094WO - MyScore29Claims1. An integrated portable digital court monitoring and scoring device (10) for tennis courts (17), comprisinga housing (11) configured to be positioned at a tennis court (17);a processing unit (12) for processing sensor data;a data communications interface (14) configured to connect the device (10) to remote data processing (20, 22) and data storage systems (18);a display unit (24) for presenting score values (26) and / or information for players and / or spectators;a scoring unit (25) with a plurality of score plates (28) with magnetic angle sensors (30) each score plate (28) being mechanically rotatable to indicate score values (26), wherein the processing unit (12) is configured to determine current score values (26) based on angular position signals from the magnetic angle sensors (30) and convert the angular position signals into corresponding score values (26);a court surface topology sensor assembly (32) comprising an ultrasonic sensor (34) configured to emit high-frequency sound waves for detecting surface height variations of the court (17);wherein the processing unit (12) is configured for generating court surface topology data (36);- a moisture sensor assembly (38) comprising an infrared sensor (40), ultraviolet radiation sensor (42), and / or ambient temperature sensor (44), the moisture sensor assembly (38) or the processing unit (12) being configured to determine a court surface moisture level;- a player presence sensor assembly (46) comprising an acoustic (48), thermal (50), PI R, laser sensor, ultrasonic (51), visual (52) and / or acceleration sensor (54) configured for detecting a presence of a player on the court;- a court usage intensity sensor assembly (56) comprising a vibration sensor (58) and / or an audio sensor (60), wherein the processing unit (12) is configured to derive a usage intensity factor from the vibration (58) and / or audio sensor (60) signals based on machine learning classification.ZP11094WO - MyScore302. Tennis monitoring and scoring device (10) according to claim 1, wherein the magnetic angle sensors (30) are GMR (Giant magnetoresistance) magnetic angle sensors associated with each score plate (28).

3. Tennis monitoring and scoring device (10) according to any of the claims 1 to 2, wherein the processing unit (12) is configured to extract gameplay-related audio features from the acoustic sensor (48) signals based on a trained machine learning model.

4. Tennis monitoring and scoring device (10) according to any of the claims 1 to 3, wherein the processing unit (12) is configured to process weather data 18) received from the data communications interface (14) and process sensor data (78) from the different sensor assemblies (32,46,56) to predict a future surface topology and / or surface moisture level for generating maintenance scheduling recommendations.

5. Tennis monitoring and scoring device (10) according to any of the claims 1 to 4, wherein the processing unit (12) is configured to generate, based on acquired sensor data (78), control data for controlling court maintenance robots.

6. Tennis monitoring and scoring device (10) according to any of the claims 1 to 5, wherein the infrared sensors (40) of the moisture sensor assembly are configured to use dual wavelength infrared signals at wavelengths optimized for water molecule absorption characteristics.

7. Tennis monitoring and scoring device (10) according to any of the claims 1 to 6, the court surface topology sensor assembly (32) further comprising a visual inspection camera (62), wherein the processing unit or camera is configured to detect surface defects using classification of the camera signals based a trained machine learning model.

8. Tennis monitoring and scoring device (10) according to any of the claims 1 to 7, wherein the temperature sensors (44) of the moisture sensor assembly (38) are configured to detect heat signatures of objects on the court surface and / or measure temperature differences between the court surface and ambient air.

9. Tennis monitoring and scoring device (10) according to any of the claims 1 to 8, wherein the data communications interface (14) is configured for transmitting the score values (26) and / or court condition data to external tournament management systems (20), booking platforms (22), and / or backend servers (16).ZP11094WO - MyScore3110. Tennis monitoring and scoring device (10) according to any of the claims 1 to 9, further comprising a solar power supply unit (64) with portable solar modules (66) which are configured to be arranged at surroundings of a tennis court (17).

11. Tennis monitoring and scoring device (10) according to any of the claims 1 to 10, wherein the scoring unit (25) is configured to receive data from sensors arranged at a player and / or tennis racket (70).

12. Tennis monitoring and scoring device (10) according to any of the claims 1 to 11, further comprising a defibrillator unit (72).

13. Tennis monitoring and scoring device (10) according to any of the claims 1 to 12, the processing unit (12) is configured to detect markers (74) on the tennis court (17) for calibrating sensors of the different sensor assemblies (32,38,46), wherein markers (74) can be detected based on image analysis, reflections of audio signals, ultrasonic signals, or electromagnetic signals, or runtime of signals.

14. Tennis monitoring and scoring device (10) according to any of the claims 1 to 13, wherein the processing unit (12) is configured to generate, based on sensor data, augmented reality data (80) for controlling an augmented reality display (82).

15. Tennis monitoring and scoring device (10) according to any of the claims 1 to 14, wherein the scoring unit (25) comprises a speech recognition unit (84) with a digital signal processor for recognizing a players speech,wherein the speech recognition unit (84) is configured to extract score values (26) from a players voice signals.

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