India 2025 July

Examples of Patentable and Not Patentable Computer Related Inventions

Given below are a non-exhaustive collection of illustrative cases to clarify which claimed inventions are patentable and which are not, based on their technical contributions and practical applications. The examples are grouped into non-excludedinventions, which deliver tangible technical solutions, and excluded inventions, whichlack such technical effects, without categorizing by specific statutory exclusions.

Patentable Inventions

1. Example: Method for Adaptive Noise Suppression in Audio Systems

Claim:

A method for minimizing background noise in an audio signal, comprising:

• a) capturing an audio input via a microphone;
• b) applying a Fast Fourier Transform (FFT) to convert the audio signal into the frequency domain;
• c) identifying and attenuating noise-related frequency components using a digital filter;
• d) reconstructing the filtered audio signal using an inverse FFT; e) delivering the noise-suppressed audio signal to a speaker.

Analysis of the Claim:

Examining the Primary Objective: The method enhances audio clarity in real-timedevices, vital for applications like hearing aids or telecommunication systems. It integrates a microphone for audio capture, a digital signal processor (DSP) executingFFT and adaptive filtering (e.g., attenuating frequencies above dynamic thresholds), and a speaker for output. The process transforms raw audio, suppresses noise in challenging environments (e.g., crowded spaces), and delivers clear sound, improvinguser experience in practical settings.

Assessing the Solution’s Nature: The FFT and filtering are computational but serve a technical workflow. The goal is delivering enhanced audio via hardware, not computation alone. The method addresses noise interference, combining microphoneinput, DSP processing, and speaker output for a tangible result, not abstract numbers.

Determining Patentability: The mathematical processing is embedded in a broader technical process of signal enhancement, resulting in a tangible, improved audio output. The method’s output is a technically enhanced signal delivered to a speaker, not an abstract number. Thus, it does not fall under the mathematical method exclusion. It is patentable because it provides a technical solution to a real-worldproblem of audio noise suppression.

2. Example: System for Autonomous Drone Navigation

Claim:

A system for autonomous drone navigation, comprising:

• a) sensors for detecting obstacles, including real-time proximity sensors (e.g., ultrasonic, LiDAR, vision sensors) to gather environmental data;
• b) a processor configured to calculate optimal flight paths using Dijkstra’s algorithm, based on sensor data, to enable autonomous navigation and obstacle avoidance duringflight.

Analysis of the Claim:

Examining the Primary Objective: The system enables drones to navigate autonomously, avoiding obstacles for applications like delivery or surveillance. It uses LiDAR (e.g., scanning at 100 Hz), ultrasonic sensors, and a processor running Dijkstra’s algorithm to compute collision-free paths in dynamic environments (e.g., urban settings with moving objects). Actuators adjust motor controls based on computed paths, ensuring safe flight.

Assessing the Solution’s Nature: Dijkstra’s algorithm is computational but supports physical drone movement. The system addresses real-time obstacle avoidance, integrating sensor data and control signals to manage hardware, achieving safe navigation rather than abstract outputs.

Determining Patentability: The mathematical computation is part of a technical process, translating into control signals that govern drone hardware. The output is tangible—safe, autonomous flight—not a mere number. Thus, it does not fall under the mathematical method exclusion. It is patentable because it delivers a technical solution to the problem of autonomous navigation.

3. Example: Method for Enhancing MRI Image Quality

Claim:

A method for enhancing MRI images, comprising:

• a) acquiring raw magnetic resonance imaging (MRI) data from an MRI scanner;
• b) denoising the data using wavelet-based techniques to suppress noise components while preserving anatomical features;
• c) reconstructing the image by transforming denoised wavelet coefficients back intothe spatial domain;
• d) displaying the enhanced image for diagnostic use on a display device.

Analysis of the Claim:

Examining the Primary Objective: The method improves MRI image clarity for medical diagnostics, enabling better visualization of anatomical structures. It uses anMRI scanner for data capture, a processor for wavelet-based denoising (e.g., discretewavelet transform to filter noise), and a display for rendering. The process removes artifacts in clinical settings (e.g., hospitals), supporting accurate diagnoses. Assessing the Solution’s Nature: Wavelet denoising is computational but part of a technical process. The goal is producing diagnostic-quality images, not abstract numbers. The method addresses image noise, integrating scanner, processor, and display for a practical outcome.

Determining Patentability: The mathematical processing is embedded in a technical process of image enhancement, resulting in a tangible, improved MRI image. The output is a diagnostic-quality image, not an abstract number. Thus, it does not fall under the mathematical method exclusion. It is patentable because it provides a technical solution to the problem of MRI image noise.

4. Example: System for Vehicle Stability Control

Claim:

A system for vehicle stability control, comprising:

• a) sensors monitoring wheel speed, vehicle speed, and steering input;
• b) a vehicle control unit calculating slip ratios using mathematical formulas, processing sensor data to detect traction loss or instability;
• c) generating control signals to adjust braking and throttle for stability, transmittingsignals to the vehicle’s braking and engine systems.

Analysis of the Claim:

Examining the Primary Objective: The system ensures vehicle stability in challenging conditions (e.g., wet roads). It employs sensors (e.g., wheel encoders, accelerometers), a control unit computing slip ratios, and actuators adjusting brakes and throttle. The process detects skidding in real-time (e.g., during sharp turns) andapplies corrections, enhancing safety.

Assessing the Solution’s Nature: Slip ratio calculations are computational but support physical vehicle control. The system addresses traction loss, using sensor dataand control signals to manage hardware, achieving a practical outcome. Determining Patentability: The mathematical computation is part of a technical process, resulting in control signals that stabilize vehicle hardware. The output is tangible stability, not a numerical result. Thus, it does not fall under the mathematical method exclusion. It is patentable because it delivers a technical solution to the problem of vehicle instability.

5. Example: Secure Data Transmission in Online Banking

Claim:

A method for securing data transmission in online banking, comprising:

• a) encrypting transaction data using a quantum-resistant cryptographic algorithmtoensure confidentiality and integrity;
• b) transmitting the encrypted data over a secure channel (e.g., TLS 1.3 or quantum- safe variant) to a banking server;
• c) authenticating the recipient using multi-factor biometric protocols.

Analysis of the Claim:

Examining the Primary Objective: The method secures online banking transactions against quantum-based attacks. It uses quantum-resistant cryptography (e.g., lattice- based algorithms), TLS 1.3 for secure channels, and biometric authentication (e.g., fingerprint and facial recognition). The process protects sensitive data in high-stakes transactions (e.g., international transfers), ensuring confidentiality and user verification.

Assessing the Solution’s Nature: The method focuses on technical security enhancements, not financial strategies. It addresses data vulnerabilities, integratingencryption, secure channels, and biometrics for a practical, secure outcome. Determining Patentability: The method integrates technical components to achievesecure data transmission, producing a tangible security effect. It does not fall under the business method exclusion, as it is not a commercial strategy but a technical solution. It is patentable because it addresses the technical challenge of secure banking transactions.

6. Example: Enhanced POS Terminal for Card Transactions

Claim:

A point-of-sale (POS) terminal, comprising:

• a) a card reader with adaptive signal processing to optimize data capture accuracy;
• b) an error-correction protocol for data transmission, using redundancy checks, forward error correction, and automatic retransmission to ensure reliable communication with the payment processor.

Analysis of the Claim:

Examining the Primary Objective: The POS terminal enhances transaction reliability through technical improvements. It features a card reader with adaptive signal processing (e.g., adjusting for magnetic stripe noise) and an error-correctionprotocol (e.g., Reed-Solomon codes). The system ensures accurate data capture inbusy retail environments, improving payment processing reliability. Assessing the Solution’s Nature: The core is technical—signal processing and error correction—not a commercial strategy. It addresses transaction data integrity, optimizing hardware performance for a practical outcome.

Determining Patentability: The system integrates technical components to achievereliable transaction processing, producing a tangible effect. It does not fall under thebusiness method exclusion, as it focuses on technical enhancements, not commercial operations. It is patentable because it provides a technical solution to transactionreliability.

7. Example: Optimized Server Load Balancing for E-commerce Platforms

Claim:

A method for balancing server load in an e-commerce platform, comprising:

• a) monitoring real-time user activity and server status, collecting data on requests, session counts, CPU/memory usage, and network latency;
• b) dynamically allocating resources using a predictive analytics engine to adjust computational resources;
• c) rerouting user requests to optimize response time, directing requests to the least loaded or geographically optimal server.

Analysis of the Claim:

Examining the Primary Objective: The method optimizes e-commerce platformperformance, ensuring fast user experiences during high traffic (e.g., sales events). It uses sensors for server metrics (e.g., CPU usage), a predictive analytics engine (e.g., machine learning for load forecasting), and a routing module. The systemminimizes delays and server crashes, enhancing reliability. Assessing the Solution’s Nature: The core is technical—resource allocation and routing—not a commercial strategy. It addresses server bottlenecks, integrating analytics and routing for a practical outcome.

Determining Patentability: The method integrates technical components to achieveoptimized server performance, producing a tangible effect. It does not fall under the business method exclusion, as it focuses on technical infrastructure, not commercial operations. It is patentable because it provides a technical solution to server loadmanagement.

8. Example: Secure Biometric Authentication for Mobile Devices

Claim:

A method for authenticating users on a mobile device, comprising:

• a) capturing a live fingerprint image using an embedded capacitive sensor;
• b) extracting a feature vector using a convolutional neural network (CNN) within a secure enclave processor;
• c) encrypting the feature vector using a hardware-based AES engine;
• d) matching the encrypted vector against stored templates;
• e) granting or denying access based on the match.

Analysis of the Claim:

Examining the Primary Objective: The method secures mobile device access through biometric authentication, preventing unauthorized access. It uses a capacitivesensor for fingerprint capture, a CNN in a secure enclave for feature extraction (e.g., 128-256 dimensional vectors), and an AES engine for encryption. The process ensures secure user verification in real-time (e.g., for mobile payments). Assessing the Solution’s Technical Realization: The CNN is implemented in a secure enclave with hardware support, addressing authentication vulnerabilities. Themethod integrates sensors, processors, and encryption for a practical security outcome. Determining Patentability: The method integrates technical components to achievesecure authentication, producing a tangible effect. It does not fall under the algorithmexclusion, as it is not an abstract process but a hardware-integrated solution. It is patentable because it provides a technical solution to mobile security.

9. Example: Real-Time Video Compression in Surveillance Cameras

Claim:

A method for compressing video streams in a surveillance camera, comprising:

• a) capturing raw video frames via a CMOS sensor;
• b) applying a motion estimation algorithm in an FPGA-based hardware accelerator;
• c) encoding frames using H.265 codec settings optimized for low-latency;
• d) transmitting the compressed video over a wireless network to a remote server.

Analysis of the Claim:

Examining the Primary Objective: The method enables efficient video streamingfor surveillance, reducing bandwidth needs. It uses a CMOS sensor for frame capture, an FPGA for motion estimation, an H.265 encoder, and a wireless module. The system supports real-time monitoring (e.g., in security operations), optimizing latencyand bandwidth.

Assessing the Solution’s Technical Realization: The motion estimation algorithmis implemented in an FPGA, addressing bandwidth constraints. The method integrates hardware for a practical streaming outcome.

Determining Patentability: The method integrates technical components to achieveefficient video compression, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a hardware-integrated solution. It is patentable because it provides a technical solution to surveillance streaming.

10. Example: Adaptive Noise Cancellation for Hearing Aids

Claim:

A hearing aid device comprising:

• a) a microphone array for capturing ambient audio signals with spatial filtering;
• b) a digital signal processor (DSP) executing an adaptive filtering algorithmto suppress noise;
• c) an amplifier and speaker delivering enhanced audio.

Analysis of the Claim:

Examining the Primary Objective: The device enhances audio clarity for hearingaid users in noisy environments (e.g., restaurants). It uses a microphone array for directional audio, a DSP for adaptive filtering (e.g., least mean squares), and an amplifier for output. The system improves speech intelligibility for users with hearingimpairments.

Assessing the Solution’s Technical Realization: The filtering algorithmis executedon a DSP, addressing noise suppression. The method integrates hardware for a practical audio outcome.

Determining Patentability: The method integrates technical components to achieveclear audio delivery, producing a tangible effect. It does not fall under the algorithmexclusion, as it is not an abstract process but a hardware-integrated solution. It is patentable because it provides a technical solution to hearing aid audio clarity.

11. Example: Dynamic Packet Routing in 5G Networks

Claim:

A method for routing packets in a 5G network, comprising:

• a) monitoring channel usage with spectrum sensors;
• b) applying a dynamic shortest-path algorithm using real-time congestion metrics;
• c) forwarding packets along the lowest-latency path;
• d) updating routing tables based on topology changes.

Analysis of the Claim:

Examining the Primary Objective:The method optimizes 5G network routing tominimize latency during high-demand scenarios (e.g., video streaming). It uses spectrum sensors for metrics (e.g., interference), a processor for shortest-path routing, and a router for table updates. The system ensures efficient data transmission in dynamic networks.

Assessing the Solution’s Technical Realization: he routing algorithmis implemented in a network system, addressing congestion. The method integrates components for a practical routing outcome.

Determining Patentability: The method integrates technical components to achieveefficient packet routing, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a hardware-integrated solution. It is patentable because it provides a technical solution to network congestion.

12. Example: Adaptive Traffic Management System

Claim:

A system for managing traffic, comprising:

• a) image sensors at intersections capturing real-time video;
• b) a central processor with a neural network analyzing vehicle density and patterns;
• c) a signal control module adjusting traffic lights based on predictions.

Analysis of the Claim:

Examining the Primary Objective: The system optimizes urban traffic flowduringpeak hours (e.g., rush hour). It uses image sensors (e.g., 1080p cameras), a neural network for density analysis (e.g., trained on traffic patterns), and a signal control module. The system reduces congestion and improves safety by adjusting lights dynamically.

Assessing the Solution’s Technical Realization: The neural network is implementedin a processor, addressing traffic congestion. The system integrates components for apractical traffic management outcome.

Determining Patentability: The system integrates technical components to achieve optimized traffic flow, producing a tangible effect. It does not fall under the algorithmexclusion, as it is not an abstract process but a hardware-integrated solution. It is patentable because it provides a technical solution to traf ic management.

13. Example: Method for Data Compression in Cloud Storage

Claim:

A method for compressing data in a cloud storage system, comprising:

• a) segmenting data streams into blocks;
• b) applying a context-aware compression algorithm selecting lossy or lossless techniques;
• c) storing compressed data across a cloud cluster with metadata for retrieval.

Analysis of the Claim:

Examining the Primary Objective: The method enhances cloud storage efficiencyfor large-scale data (e.g., enterprise backups). It uses a processor for data segmentation, context-aware compression (e.g., JPEG for images, ZIP for text), andmetadata storage. The system optimizes storage and bandwidth in distributed environments.

Assessing the Solution’s Technical Realization: The compression algorithmis implemented in a cloud system, addressing storage efficiency. The method integrates components for a practical outcome.

Determining Patentability: The method integrates technical components to achieveefficient data compression, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to cloud storage ef iciency.

14. Example: Method for Correcting Transmission Errors in Wireless Communication

Claim:

A method for correcting transmission errors in wireless communication, comprising:

• a) encoding packets with adaptive error-correcting codes (e.g., Reed-Solomon, LDPC);
• b) detecting errors using a parity-check module;
• c) retransmitting erroneous segments based on feedback.

Analysis of the Claim:

Examining the Primary Objective: The method improves wireless communicationreliability in noisy environments (e.g., urban Wi-Fi). It uses a processor for encoding, a parity-check module for error detection, and a feedback system for retransmission. The system ensures data integrity during high-traffic scenarios.

Assessing the Solution’s Technical Realization: The error-correcting algorithmis implemented in a communication system, addressing data loss. The method integrates components for a practical outcome.

Determining Patentability: The method integrates technical components to achievereliable communication, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to transmission errors.

15. Example: Method for Efficient Memory Management in Embedded Systems

Claim:

A method for managing memory in an embedded device, comprising:

• a) monitoring memory usage patterns in real-time;
• b) predicting future needs with an allocation algorithm;
• c) compacting memory to reduce fragmentation.

Analysis of the Claim:

Examining the Primary Objective: The method optimizes memory in resource- constrained embedded devices (e.g., IoT sensors). It uses a monitoring module for usage patterns, a predictive algorithm for allocation, and a compaction module. The system enhances performance in low-memory environments.

Assessing the Solution’s Technical Realization: The algorithms are implementedinan embedded system, addressing memory fragmentation. The method integrates components for a practical outcome.

Determining Patentability: The method integrates technical components to achieveefficient memory management, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to memory optimization.

16. Example: Method for Securing IoT Device Communication

Claim:

• a) establishing a PKI-based authentication protocol;
• b) encrypting data packets with a lightweight cryptographic algorithm;
• c) rotating encryption keys periodically to prevent replay attacks.

Analysis of the Claim:

Examining the Primary Objective: The method secures IoT communication in smart home systems (e.g., connected thermostats). It uses PKI for authentication, lightweight cryptography (e.g., elliptic curve), and key rotation protocols. The systemprevents unauthorized access in resource-constrained networks.

Assessing the Solution’s Technical Realization:The cryptographic algorithms are implemented in IoT devices, addressing security challenges. The method integrates components for a practical outcome.

Determining Patentability: The method integrates technical components to achievesecure communication, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to IoT security.

17. Example: System for Automated Drone-Based Crop Monitoring

Claim:

A system for automated crop monitoring, comprising:

• a) a drone with multispectral cameras capturing images;
• b) a processor analyzing images with vegetation indices and machine learning;
• c) a reporting module generating actionable insights for farmers.

Analysis of the Claim:

Examining the Primary Objective: The system automates crop health monitoringinlarge farms. It uses multispectral cameras (e.g., capturing infrared bands), a processor with machine learning (e.g., NDVI analysis), and a reporting module. The systemdetects stress or disease, enhancing agricultural productivity.

Assessing the Solution’s Technical Realization: The algorithms are implementedina drone system, addressing manual inspection challenges. The systemintegrates components for a practical outcome.

Determining Patentability: The system integrates technical components to achieveautomated crop monitoring, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to agricultural monitoring.

18. Example: System for Real-Time Fraud Detection in Financial Transactions

Claim:

A system for detecting fraud in financial transactions, comprising:

• a) a transaction monitoring module capturing data from multiple channels;
• b) a processor with a machine learning model detecting anomalies;
• c) an alert module flagging suspicious transactions.

Analysis of the Claim:

Examining the Primary Objective: The system detects fraud in real-time across banking channels (e.g., online payments). It uses a monitoring module for data (e.g., transaction location), a machine learning model for anomaly detection, and an alert module. The system reduces losses by identifying fraud quickly.

Assessing the Solution’s Technical Realization: The machine learning algorithmis implemented in a processor, addressing fraud detection challenges. The systemintegrates components for a practical outcome.

Determining Patentability: The system integrates technical components to achievefraud detection, producing a tangible effect. It does not fall under the algorithmexclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to financial security.

19. Example: Method for Efficient Spectrum Allocation in Wireless Networks

Claim:

A method for allocating spectrum in a wireless network, comprising:

• a) monitoring channel usage with spectrum sensors;
• b) dynamically assigning frequencies using a demand-aware algorithm;
• c) resolving conflicts with an interference management algorithm.

Analysis of the Claim:

Examining the Primary Objective: The method optimizes spectrumallocation inwireless networks (e.g., cellular networks). It uses sensors for channel metrics, a processor for dynamic allocation, and an interference management module. The system enhances throughput during peak usage.

Assessing the Solution’s Technical Realization: The algorithms are implementedina network system, addressing spectrum congestion. The method integrates components for a practical outcome.

Determining Patentability: The method integrates technical components to achieveefficient spectrum allocation, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to network ef iciency.

20. Example: System for Real-Time Network Intrusion Detection

Claim:

A system for detecting network intrusions, comprising:

• a) a packet inspection module capturing network traffic data;
• b) a processor with a deep learning model identifying anomalies;
• c) an alert module notifying administrators of threats.

Analysis of the Claim:

Examining the Primary Objective: The system secures networks against cyberattacks (e.g., DDoS) in real-time. It uses a packet inspection module for traffic data (e.g., IP packets), a deep learning model for anomaly detection, and an alert module. The system protects enterprise networks effectively.

Assessing the Solution’s Technical Realization: The deep learning algorithmis implemented in a processor, addressing security challenges. The systemintegrates components for a practical outcome.

Determining Patentability: The system integrates technical components to achievenetwork security, producing a tangible effect. It does not fall under the algorithm exclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to network intrusion detection.

21. Example: Method for Hierarchical Token-Based Secure Access for Industrial Automation

Claim:

A method for managing secure access to an industrial automation system, comprising:

• a) establishing a secure communication channel;
• b) providing a zone access token for general access;
• c) generating a time-limited device command token for specific actuator control;
• d) validating tokens for command execution.

Analysis of the Claim:

Examining the Primary Objective: The method secures remote access to industrial systems (e.g., factory robots). It uses a secure channel (e.g., TLS), zone access tokens, and time-limited command tokens for actuators. The system prevents unauthorizedcommands in distributed networks.

Assessing the Solution’s Technical Realization: The token-based algorithms are implemented in a control server, addressing secure access challenges. The methodintegrates components for a practical outcome.

Determining Patentability: The method integrates technical components to achievesecure access, producing a tangible effect. It does not fall under the algorithmexclusion, as it is not an abstract process but a system-integrated solution. It is patentable because it provides a technical solution to industrial systemsecurity.

Excluded Inventions, Not Patentable

22. Example: Method for Calculating Compound Interest

Claim:

A method comprising:

• a) receiving principal, rate, and time inputs from a user or external system;
• b) applying the compound interest formula ( A = P \times (1 + r / n)^{n \times t} ), where ( A ) is the final amount, ( P ) is the principal, ( r ) is the annual interest rate, ( n ) is the compounding frequency, and ( t ) is the time in years;
• c) outputting the calculated final amount to the user or another system.

Analysis of the Claim:

Examining the Primary Objective: The method automates compound interest calculations for financial planning (e.g., loan assessments). It uses a processor to apply the formula, receiving inputs via an interface and displaying results. The systemfocuses on numerical outputs for financial decisions, without technical integration.

Assessing the Solution’s Nature: The core is a mathematical computation, producingabstract results. The method lacks technical application (e.g., hardware optimization), focusing solely on financial calculations without enhancing system functionality.

Determining Patentability: The method produces a numerical result without technical application, fitting the mathematical method exclusion. It is not patentablebecause it is an abstract computation lacking a technical ef ect or systemintegration.

23. Example: System for Statistical Data Analysis

Claim:

A system comprising:

• a) receiving a dataset from a user or external source;
• b) applying regression analysis to compute correlation coefficients, describing relationships between variables;
• c) outputting the coefficients for user display or export.

Analysis of the Claim:

Examining the Primary Objective: The system performs statistical analysis for datainterpretation (e.g., market research). It uses a processor for regression analysis, accepting datasets via an interface and displaying coefficients. The systemfocuses onnumerical outputs for statistical use, without technical context.

Assessing the Solution’s Nature: The regression analysis is computational, producing abstract coefficients. The system lacks hardware integration or technical enhancement, focusing on statistical computation without practical application.

Determining Patentability: The system produces abstract numerical outputs, fitting the mathematical method exclusion. It is not patentable because it is an abstract computation lacking a technical ef ect or system integration.

24. Example: Method for Generating Random Numbers

Claim:

A method comprising:

• a) receiving a seed value via an input module;
• b) applying a mathematical formula (e.g., linear congruential generator) to compute asequence of random numbers;
• c) outputting the sequence for user or system use.

Analysis of the Claim:

Examining the Primary Objective: The method generates random numbers for simulations (e.g., modeling). It uses a processor to apply a formula, accepting a seedand outputting numbers. The system focuses on numerical sequences without technical application (e.g., in cryptography).

Assessing the Solution’s Nature: The core is a mathematical computation, producingabstract results. The method lacks technical specifics or system integration, focusingsolely on number generation.

Determining Patentability: The method produces an abstract numerical sequence, fitting the mathematical method exclusion. It is not patentable because it is anabstract computation lacking a technical ef ect or system integration.

25. Example: Method for Solving Quadratic Equations

Claim:

A method comprising:

• a) receiving coefficients ( a, b, c ) for a quadratic equation ( a x^2 + b x + c = 0 );
• b) applying the quadratic formula ( x = \frac{-b \pm \sqrt{b^2 - 4 a c}}{2 a} ) to compute roots;
• c) outputting the roots for display or transmission.

Analysis of the Claim:

Examining the Primary Objective: The method automates solving quadratic equations for educational purposes (e.g., math tutoring). It uses a processor to applythe formula, receiving coefficients and displaying roots. The system focuses on numerical solutions without technical context.

Assessing the Solution’s Nature: The core is a mathematical computation, producingabstract roots. The method lacks technical application or system enhancement, focusing solely on calculation.

Determining Patentability: The method produces numerical roots without technical application, fitting the mathematical method exclusion. It is not patentable because it is an abstract computation lacking a technical ef ect or system integration.

26. Example: Tiered Bank Service Fee Calculation

Claim:

A method for calculating and applying tiered service fees in a bank, comprising:

• a) determining a customer’s account balance and transaction volume;
• b) applying business rules to assign fees based on activity;
• c) debiting the calculated fee from the customer’s account.

Analysis of the Claim:

Examining the Primary Objective: The method automates bank fee calculations for revenue optimization (e.g., retail banking). It uses a processor to retrieve balance andtransaction data, apply fee rules, and debit accounts. The system focuses on financial management without technical enhancements.

Assessing the Solution’s Nature: The core is a commercial strategy, not a technical improvement. The system uses standard hardware for financial automation, lackingtechnical contributions.

Determining Patentability: The method focuses on a commercial scheme, fittingthebusiness method exclusion. It is not patentable because it is a financial strategy lacking a technical ef ect or system enhancement.

27. Example: Customer Loyalty Program Management

Claim:

A method for managing a loyalty rewards program, comprising:

• a) tracking customer purchases to calculate points based on frequency and value;
• b) assigning membership levels (e.g., Silver, Gold, Platinum) based on points;
• c) providing exclusive discounts to higher-tier members.

Analysis of the Claim:

Examining the Primary Objective: The method manages a loyalty programto boost customer retention (e.g., in retail). It uses a processor to track purchases, calculate points, and assign tiers, offering discounts. The system focuses on marketing without technical enhancements.

Assessing the Solution’s Nature: The core is a marketing strategy, not a technical improvement. The system uses standard hardware for administrative automation, lacking technical contributions.

Determining Patentability: The method focuses on a commercial scheme, fittingthebusiness method exclusion. It is not patentable because it is a marketing strategy lacking a technical ef ect or system enhancement.

28. Example: Dynamic Pricing Strategy for Ride-Sharing Services

Claim:

A method for dynamically adjusting ride fares, comprising:

• a) monitoring real-time demand and supply of vehicles;
• b) applying business rules to set surge pricing rates based on demand-supply ratios;
• c) updating fare quotes in the app for user confirmation.

Analysis of the Claim:

Examining the Primary Objective: The method optimizes ride-sharing revenue through dynamic pricing (e.g., during peak hours). It uses a server to monitor vehicleand request data, apply pricing rules, and update app displays. The systemfocuses onpricing strategy without technical enhancements.

Assessing the Solution’s Nature: The core is a commercial strategy, not a technical improvement. The system uses standard hardware for pricing automation, lackingtechnical contributions.

Determining Patentability: The method focuses on a commercial scheme, fittingthebusiness method exclusion. It is not patentable because it is a pricing strategy lacking a technical ef ect or system enhancement.

29. Example: Generic Sorting Algorithm

Claim:

A method for sorting a list of numbers, comprising:

• a) selecting a pivot element;
• b) partitioning the list into sublists based on the pivot;
• c) recursively sorting sublists;
• d) combining sorted sublists.

Analysis of the Claim:

Examining the Primary Objective: The method automates sorting numbers (e.g., quicksort for data processing). It uses a processor for partitioning and sorting, producing an ordered list. The system focuses on abstract computation without technical application.

Assessing the Solution’s Technical Realization: The steps are abstract, lacking hardware integration or technical context (e.g., database optimization). The methodfocuses solely on sorting without enhancing systems.

Determining Patentability: The method produces an abstract algorithm, fitting the algorithm exclusion. It is not patentable because it is an abstract computational process lacking a technical ef ect or system integration.

30. Example: Text Tokenization Algorithm

Claim:

A method for tokenizing a text string, comprising:

• a) scanning for delimiter characters;
• b) splitting the string into tokens;
• c) outputting the list of tokens.

Analysis of the Claim:

Examining the Primary Objective: The method breaks text into tokens for data processing (e.g., text analysis). It uses a processor to scan and split text, producinga token list. The system focuses on abstract computation without technical context.

Assessing the Solution’s Technical Realization: The steps are abstract, lacking integration (e.g., in speech recognition). The method focuses solely on tokenization without enhancing systems.

Determining Patentability: The method produces an abstract algorithm, fitting the algorithm exclusion. It is not patentable because it is an abstract computational process lacking a technical ef ect or system integration.

31. Example: Method for Scheduling Employee Shifts

Claim:

A method for scheduling employee shifts, comprising:

• a) receiving employee availability via a user interface;
• b) generating schedules using predefined business rules;
• c) notifying employees of assigned shifts.

Analysis of the Claim:

Examining the Primary Objective: The method automates shift scheduling for efficiency (e.g., in retail). It uses a processor to collect availability, apply rules (e.g., labor laws), and send notifications. The system focuses on administrative automationwithout technical enhancements.

Assessing the Solution’s Technical Realization: The scheduling uses standard software, lacking technical innovation. The method automates a non-technical taskwithout system improvements.

Determining Patentability: The method focuses on administrative automation, fitting the computer programme per se exclusion. It is not patentable because it is anon-technical process lacking a technical ef ect or system enhancement.

32. Example: System for Generating Business Reports

Claim:

A system for generating business reports, comprising:

• a) a module collecting sales data from various sources;
• b) a module formatting and displaying reports;
• c) a module exporting reports to PDF.

Analysis of the Claim:

Examining the Primary Objective: The system automates business report generation (e.g., for sales analysis). It uses software to collect data, format reports (e.g., charts), and export to PDF. The system focuses on administrative automationwithout technical enhancements.

Assessing the Solution’s Technical Realization: The modules use standard software, lacking technical innovation. The system automates a non-technical task without system improvements.

Determining Patentability: The system focuses on administrative automation, fittingthe computer programme per se exclusion. It is not patentable because it is a non technical process lacking a technical ef ect or system enhancement.

33. Example: Method for Creating Digital Art

Claim:

A method for generating digital art, comprising:

• a) selecting a color palette;
• b) applying randomization to generate patterns;
• c) displaying the resulting image.

Analysis of the Claim:

Examining the Primary Objective: The method automates digital art creation for aesthetics (e.g., for galleries). It uses a processor to select colors, apply randomization, and display images. The system focuses on creative automation without technical enhancements.

Assessing the Solution’s Technical Realization: The randomization is abstract, lacking technical integration. The method automates a non-technical task without system improvements.

Determining Patentability: The method focuses on creative automation, fitting the computer programme per se exclusion. It is not patentable because it is a non technical process lacking a technical ef ect or system enhancement.

34. Example: System for Managing Personal Finances

Claim:

A system for managing personal finances, comprising:

• a) a module for recording expenses;
• b) a module for generating budgets;
• c) a module for displaying spending charts.

Analysis of the Claim:

Examining the Primary Objective: The system automates personal finance management (e.g., budgeting apps). It uses software to record expenses, calculate budgets, and display charts. The system focuses on administrative automation without technical enhancements.

Assessing the Solution’s Technical Realization: The modules use standard software, lacking technical innovation. The system automates a non-technical task without system improvements.

Determining Patentability: The system focuses on administrative automation, fittingthe computer programme per se exclusion. It is not patentable because it is a non technical process lacking a technical ef ect or system enhancement.

35. Example: Method for Generating Music Playlists

Claim:

A method for generating music playlists, comprising:

• a) receiving user genre preferences;
• b) selecting songs from a music database;
• c) creating a playlist for playback.

Analysis of the Claim:

Examining the Primary Objective: The method automates playlist creation for entertainment (e.g., streaming apps). It uses a processor to collect preferences, queryadatabase, and compile playlists. The system focuses on entertainment automation without technical enhancements.

Assessing the Solution’s Technical Realization: The filtering uses standard software, lacking technical innovation. The method automates a non-technical task without system improvements.

Determining Patentability: The method focuses on entertainment automation, fittingthe computer programme per se exclusion. It is not patentable because it is a non technical process lacking a technical ef ect or system enhancement.

36. Example: System for Generating Invoices

Claim:

• a) a module for entering customer and product data;
• b) a module for calculating totals with taxes or discounts;
• c) a module for exporting invoices to PDF.

Analysis of the Claim:

Examining the Primary Objective: The system automates invoice creation for business efficiency (e.g., small businesses). It uses software to input data, calculate totals, and export to PDF. The system focuses on administrative automation without technical enhancements.

Assessing the Solution’s Technical Realization: The modules use standard software, lacking technical innovation. The system automates a non-technical task without system improvements.

Determining Patentability: The system focuses on administrative automation, fittingthe computer programme per se exclusion. It is not patentable because it is a non technical process lacking a technical ef ect or system enhancement.

37. Example: Method for Scheduling Social Media Posts

Claim:

A method for scheduling social media posts, comprising:

• a) receiving post content and desired time;
• b) storing the post in a queue;
• c) automatically posting at the scheduled time via APIs.

Analysis of the Claim parlty:

Examining the Primary Objective: The method automates social media postingfor consistency (e.g., marketing campaigns). It uses a processor to collect content, manage a queue, and post via APIs. The system focuses on administrative automationwithout technical enhancements.

Assessing the Solution’s Technical Realization: The queuing uses standard software, lacking technical innovation. The method automates a non-technical task without system improvements.

Determining Patentability: The method focuses on administrative automation, fitting the computer programme per se exclusion. It is not patentable because it is anon-technical process lacking a technical ef ect or system enhancement.

38. Example: Method for Generating Sudoku Puzzles

Claim:

A method for generating Sudoku puzzles, comprising:

• a) selecting numbers based on predefined rules;
• b) arranging numbers in a grid ensuring solvability;
• c) outputting the puzzle.

Analysis of the Claim:

Examining the Primary Objective: The method automates Sudoku puzzle creationfor entertainment (e.g., mobile apps). It uses a processor to select and arrange numbers, ensuring solvability. The system focuses on creative automation without technical enhancements.

Assessing the Solution’s Technical Realization: The generation is abstract, lackingtechnical integration. The method automates a non-technical task without systemimprovements.

Determining Patentability: The method focuses on creative automation, fitting the computer programme per se exclusion. It is not patentable because it is a non technical process lacking a technical ef ect or system enhancement.

39. Example: System for Managing Customer Loyalty Points

Claim:

A system for managing loyalty points, comprising:

• a) a module for recording purchases;
• b) a module for calculating points based on rules;
• c) a module for redeeming points for rewards.

Analysis of the Claim:

Examining the Primary Objective: The system automates loyalty point management for customer retention (e.g., retail programs). It uses software to recordpurchases, calculate points, and process redemptions. The system focuses on business automation without technical enhancements.

Assessing the Solution’s Technical Realization: The modules use standard software, lacking technical innovation. The system automates a non-technical task without system improvements.

Determining Patentability: The system focuses on business automation, fitting the computer programme per se exclusion. It is not patentable because it is a non technical process lacking a technical ef ect or system enhancement.

40. Example: Method for Generating Email Templates

Claim:

A method for generating email templates, comprising:

• a) selecting a template from a database;
• b) entering recipient-specific data;
• c) sending the email using standard protocols (e.g., SMTP).

Analysis of the Claim:

Examining the Primary Objective: The method automates email template creationfor communication (e.g., marketing emails). It uses a processor to select templates, insert data, and send emails. The system focuses on administrative automation without technical enhancements.

Assessing the Solution’s Technical Realization: The process uses standard software, lacking technical innovation. The method automates a non-technical task without system improvements.

Determining Patentability: The method focuses on administrative automation, fitting the computer programme per se exclusion. It is not patentable because it is anon-technical process lacking a technical ef ect or system enhancement.