Novel device contact information management framework & associated features

Abstract

The present disclosure relates to a system and method for Al-driven intelligent contact management, privacy enforcement, and dynamic communication control in mobile devices. The system comprises an Al-powered processing unit configured to analyze contact usage patterns, categorize contacts into adaptive groups, and automate the deletion of temporary or redundant entries. A Pattern Recognition System detects frequent, inactive, or spam contacts, while a Blockchain Security Module ensures tamper-proof access logs and secure app permission management. The AI-Based Privacy Enforcement System dynamically restricts unauthorized access to contact data, enforces user-defined privacy settings, and integrates with selective Silent Mode, Do Not Disturb (DND), and call filtering configurations. The system further enables loT-based contact synchronization, ensuring seamless multi-device privacy control and communication optimization. By integrating machine learning, predictive analytics, and decentralized security, the present invention enhances privacy, security, and efficiency in mobile contact management.

Description

TECHNICAL FIELD

[0001] The present invention relates to a system and method for intelligent contact management in mobile devices, enabling efficient organization, access control, and automated maintenance of contact information. More particularly, the invention pertains to Al-driven contact categorization, automated contact cleanup, privacy-enhanced contact accessibility, and dynamic configuration of device features such as silent mode, Do Not Disturb (DND), and call blocking based on contact groups. The system leverages Al, predictive analytics, and blockchain-based security mechanisms to enhance user privacy, prevent unauthorized access, and provide an adaptive, user-friendly approach to managing personal and professional contacts.BACKGROUND

[0002] In the rapidly evolving landscape of mobile communication and smartphone applications, managing personal and professional contacts efficiently has become increasingly important. Mobile devices store a vast number of contact entries, including frequently used, temporary, and outdated numbers. Various smartphone applications, such as messaging apps and social media platforms, access these contacts to enable their services. However, unrestricted access to all saved contacts poses privacy concerns, security risks, and inefficiencies in handling communication across different domains (personal, professional, temporary, etc.). Furthermore, users lack intelligent mechanisms to manage contacts dynamically, leading to cluttered contact lists, redundant entries, and unintended information sharing.

[0003] Conventional methods available for contact management primarily involve manual grouping, static contact lists, and basic organization tools. While some smartphones offer features like contact groups, favorites, and call blocking, these methods lack automation, intelligent classification, and adaptive privacy controls. Additionally, contact lists often accumulate obsolete or unused numbers, as there is no built-in mechanism to detect and remove them systematically. Many users also save temporary numbers for short-term use (e.g., delivery personnel, customer service calls) but forget to delete them, resulting in permanent retention of unnecessary contacts. Moreover, existing Silent Mode, DND, and call blocking features apply universally rather than being selectively configured for specific groups, making them inefficient for personalized communication management.

[0004] To address these technical problems, a smart and automated contact management system is required to categorize, update, and optimize contacts dynamically while ensuring enhanced privacy, security, and user control over contact-based smartphone functionalities. There is also a need for Al-driven automation to analyze contact usage patterns, suggest deletions or updates, and enable selective privacy configurations for different applications. Furthermore, intelligent filtering of calls and messages based on contextual priorities can significantly enhance the user experience by reducing unnecessary disturbances and maintaining seamless communication.

[0005] As a result, there is a need for a system and method for intelligent contact management, privacy control, and dynamic feature configuration in mobile devices. Such a system should enable Al-powered contact organization, predictive deletion of unused contacts, selective app access for different contact groups, and personalized feature settings for Silent Mode, DND, and call blocking. Additionally, the system should incorporate blockchain-based security mechanisms to prevent unauthorized access to contact data while offering user-configurable, adaptive contact management solutions for improved privacy, security, and efficiency.SUMMARY

[0006] In an embodiment, a method for intelligent contact management in mobile devices comprises Al-driven contact classification, automated contact cleanup, selective privacy controls, and dynamic feature configurations. The method includes detecting unused contacts based on predefined time thresholds, categorizing contacts into adaptive groups (e.g., Family, Professional, Temporary), and enabling selective access control for different smartphone applications. The processor executes machine learning algorithms to analyze contact usage patterns, predict deletions, and suggest relevant contact groupings. The processor dynamically configures silent mode, Do Not Disturb (DND), and call blocking for specific contact groups, ensuring customized communication preferences. Additionally, temporary contact lists are automatically purged after a configurable period, reducing unnecessary data retention and improving privacy. The processor integrates blockchain-backed access logs, allowing users to monitor and revoke app permissions dynamically to enhance security. Further, the system leverages loT connectivity to synchronize contact preferences across multiple user devices, ensuring a seamless and personalized experience. Through predictive analytics and automated decision-making, the method minimizes manual interventions and optimizes the efficiency, privacy, and usability of mobile contact management.

[0007] In an embodiment, a system for intelligent contact management in mobile devices comprises a processor, memory, Al-driven contact classification module, privacy control module, automated cleanup engine, and dynamic feature configuration unit. The system is configured to analyze contact usage patterns, categorize contacts into adaptive groups (e.g., Family, Professional, Temporary), and enable selective access control for applications. In an embodiment, the system integrates an AI- based predictive analytics engine to detect unused or redundant contacts based on predefined time thresholds and trigger automated deletions or user alerts for review. The processor dynamically manages silent mode, Do Not Disturb (DND), and call blocking settings, applying them selectively to predefined contact groups for personalized communication management. Additionally, the system includes a temporary contact handling module, which stores contacts for short-term use and automatically deletes them after a configured period to maintain privacy and avoid unnecessary data retention. The system further integrates a blockchain-backed access control mechanism, ensuring secure logging, monitoring, and revocation of app permissions dynamically to prevent unauthorized access. The processor also enables loT-based synchronization, allowing users to manage contact preferences seamlessly across multiple devices. Through machine learning-based decision-making, contextual automation, and real-time user-driven configurability, the system optimizes privacy, security, and efficiency in mobile contact management, enhancing overall user experience.BRIEF DESCRIPTION OF DRAWINGS

[0008] The accompanying drawings illustrate the various embodiments of systems, methods, and other aspects of the disclosure. Any person with ordinary skills in the art will appreciate that the illustrated element boundaries (e.g., boxes, groups of boxes, or other shapes) in the figures represent one example of the boundaries. In some examples, one element may be designed as multiple elements, or multiple elements may be designed as one element. In some examples, an element shown as an internal component of one element may be implemented as an external component in another, and vice versa. Further, the elements may not be drawn to scale.

[0009] Various embodiments will hereinafter be described in accordance with the appended drawings, which are provided to illustrate and not to limit the scope in any manner, wherein similar designations denote similar elements, and in which:

[0010] FIG. 1 is a block diagram illustrating the system environment (100) in which various embodiments of the present invention may be implemented.

[0011] FIG. 2 is a block diagram illustrating the architecture of the Al-powered processing unit (106), configured for real-time contact usage analysis, adaptive contact grouping, blockchain- backed access control, and predictive contact retention management, in accordance with an embodiment of the present invention.

[0012] FIG. 3 is a flowchart (300) that illustrates a method for Al-powered automated contact classification, temporary contact handling, selective silent mode configuration, and personalized Do Not Disturb (DND) settings, in accordance with an embodiment of the present invention.

[0013] FIG. 4 is a flowchart (400) that illustrates how the processor (202) is configured to execute Al- driven contact filtering, predictive contact expiration, real-time privacy protection, and dynamic feature control for communication applications, in accordance with an embodiment of the present invention.DETAILED DESCRIPTION

[0014] The present disclosure may be best understood with reference to the detailed figures and description set forth herein. Various embodiments are discussed below with reference to the figures. However, those skilled in the art will readily appreciate that the detailed descriptions given herein with respect to the figures are simply for explanatory purposes as the methods and systems may extend beyond the described embodiments. For example, the teachings presented and the needs of a particular application may yield multiple alternative and suitable approaches to implement the functionality of any detail described herein. Therefore, any approach may extend beyond the particular implementation choices in the following embodiments described and shown.

[0015] The present disclosure addresses the limitations of conventional contact management systems, which rely on static contact lists, manual organization, and lack intelligent automation, leading to privacy concerns, redundant contacts, and inefficient communication handling. The system introduces an Al-driven intelligent contact management framework that dynamically categorizes contacts, predicts and removes obsolete entries, and optimizes app access permissions based on user-defined preferences and behavioral patterns. The system leverages machine learning algorithms to analyze contact usage frequency, suggest groupings, and automate deletions for temporary or inactive contacts, reducing clutter and improving efficiency. The system further integrates blockchain-backed security mechanisms, ensuring tamper-proof access logs and dynamic permission control, allowing users to monitor and revoke third-party app access in real time.Additionally, the system enhances silent mode, Do Not Disturb (DND), and call-blocking functionalities by enabling selective configuration for specific contact groups, ensuring personalized and context-aware communication management. By incorporating loT-based synchronization, the system allows seamless cross-device contact management, while predictive analytics ensure proactive organization and automated privacy protection. Through these advancements, the present invention optimizes mobile contact handling, enhances security, and provides a more personalized and automated user experience.

[0016] The primary objective of the present invention is to overcome the limitations of conventional contact management systems by introducing an intelligent, Al-driven framework that enhances contact organization, privacy control, and communication efficiency in mobile devices. To achieve this, the present disclosure aims to dynamically categorize contacts into adaptive groups, automate contact retention and deletion, and provide selective access control for applications and smartphone features. The system's objective is to analyze user interaction patterns, detect unused or temporary contacts, and optimize their management through Al-powered predictive analysis. Additionally, the present disclosure seeks to enhance privacy by implementing blockchain-backed security mechanisms that enable real-time monitoring and revocation of app permissions, preventing unauthorized access to contact information. The system further aims to introduce an advanced silent mode, Do Not Disturb (DND), and call filtering mechanism that can be configured for specific contact groups, ensuring that users receive only relevant and high-priority communications based on context and preference. Furthermore, the present disclosure proposes a seamless loT-based synchronization model, allowing users to maintain consistent contact preferences across multiple devices. By integrating machine learning, predictive analytics, and secure decentralized storage, the invention provides an adaptive, privacy-focused, and automation-driven contact management system that significantly enhances the user experience.

[0017] The present invention introduces an Al-driven intelligent contact management system that optimizes contact organization, privacy control, and communication efficiency in mobile devices through machine learning, predictive analytics, blockchain security, and loT-based synchronization. Unlike conventional static contact lists, the system dynamically categorizes contacts into adaptive groups (e.g., Family, Professional, Temporary), predicts and removes obsolete entries, and provides selective access control for applications and smartphone features. The invention incorporates temporary contact handling with automated expiration, ensuring short-term contacts are deleted after a configurable period, thereby enhancing privacy and reducing unnecessary data retention. AI-powered predictive contact retention mechanism analyzes usage patterns, suggests deletions for inactive contacts, and alerts users about important but infrequently used numbers, thereby maintaining an optimized and clutter-free contact list. Additionally, the system introduces selective silent mode, Do Not Disturb (DND), and call filtering configurations, allowing users to apply these settings to specific contact groups rather than the entire phone, thereby ensuring customized and context-aware communication control. The blockchain-based security framework prevents unauthorized access to contact information by maintaining encrypted access logs and allowing realtime revocation of app permissions, significantly enhancing data privacy and security. Furthermore, the system seamlessly synchronizes contact preferences across multiple devices using loT connectivity, ensuring a consistent and personalized user experience. Its Al-powered contact optimization, blockchain-secured privacy protection, predictive analytics for contact retention, and adaptive silent mode configurations, which collectively improve usability, automation, and security in mobile contact management, making it a groundbreaking advancement over existing contact handling systems.

[0018] FIG. 1 is a block diagram illustrating the system environment (100) in which various embodiments of the present invention may be implemented. The system environment (100) generally comprises an Al-driven intelligent contact management module (102), a central contact optimization server (104), an Al-powered processing unit (106), a blockchain-backed security module (108), and a dynamic privacy control interface (110). The Al-driven intelligent contact management module (102) is responsible for categorizing contacts into adaptive groups, predicting and removing obsolete entries, and enabling selective access control for smartphone applications and device features. The central contact optimization server (104) facilitates real-time synchronization of contact preferences across multiple devices and ensures context-aware management of silent mode, Do Not Disturb (DND), and call filtering configurations. The AI- powered processing unit (106) analyzes contact usage patterns, automates temporary contact expiration, and provides predictive contact retention alerts to optimize communication efficiency. The blockchain-backed security module (108) ensures secure, tamper-proof access logs for monitoring and revoking third-party app permissions, thereby enhancing user privacy. The dynamic privacy control interface (110) allows users to configure selective silent mode, call blocking, and app-specific contact access settings for a personalized and secure communication experience. Together, these components enable automated, adaptive, and privacy-focused contact management, making the system an innovative and efficient solution for modern mobile devices.

[0019] As according to the present invention, the Intelligent Contact Management Module (102) is an Al-driven system component designed to optimize, categorize, and dynamically manage contact information within a mobile device. This module leverages machine learning algorithms to analyze contact usage patterns, detect redundant or obsolete entries, and automate temporary contact expiration to prevent unnecessary data retention. It enables real-time contact grouping into adaptive categories such as Family, Professional, Temporary, and Other Contacts, ensuring efficient organization and selective app access control. The module also integrates predictive analytics to provide proactive contact retention alerts, notifying users about infrequently used but important contacts, while automatically suggesting deletions for outdated numbers. Additionally, it enhances user privacy by restricting temporary contacts from accessing certain applications and features (e.g., WhatsApp status visibility). By incorporating context-aware communication settings, the Intelligent Contact Management Module (102) dynamically interacts with other system components to configure silent mode, Do Not Disturb (DND), and call blocking based on user-defined preferences for specific contact groups, thereby ensuring a personalized, automated, and secure mobile communication experience.

[0020] As according to the present invention, the Central Contact Optimization Server (104) is a cloud-based or on-device Al-powered system that facilitates real-time synchronization, optimization, and predictive management of contact information across multiple user devices. It serves as the processing hub for analyzing contact usage behavior, updating adaptive contact groupings, and enforcing privacy settings dynamically. The server leverages machine learning algorithms to detect inactive or redundant contacts, suggest automated deletions and optimize selective app access based on user interaction patterns. Additionally, it ensures seamless contact synchronization across multiple devices, allowing users to maintain a consistent contact management experience. The server also supports context-aware automation for silent mode, Do Not Disturb (DND), and call filtering, ensuring that these settings are applied dynamically based on predefined contact groups and real-time user behavior. Furthermore, it integrates with the blockchain-backed security module (108) to enable secure access logging, app permission monitoring, and revocation control, thereby enhancing data privacy and security. By providing intelligent contact handling, predictive optimization, and multi-device synchronization, the Central Contact Optimization Server (104) plays a crucial role in making contact management more automated, privacy-centric, and user-friendly.

[0021] As according to the present invention, the Al -Powered Processing Unit (106) is a computational module responsible for executing machine learning algorithms, predictive analytics, and automated decision-making to optimize contact management, privacy control, and communication efficiency in mobile devices. This unit continuously analyzes contact usage patterns, identifying frequently used, redundant, or obsolete contacts, and automates categorization, retention, or deletion based on user-defined parameters. It dynamically allocates contacts into adaptive groups (e.g., Family, Professional, Temporary) and ensures that only relevant contacts are granted access to specific applications while restricting unintended exposure of user activity. The Al-powered processing unit (106) also facilitates real-time configuration of silent mode, Do Not Disturb (DND), and call filtering, ensuring that context-based communication preferences are maintained for different user scenarios. Additionally, it integrates with the blockchain-backed security module (108) to track and control third-party app permissions, preventing unauthorized access to contact information. By leveraging predictive Al models, this unit enhances data privacy, reduces manual intervention, and enables automated, intelligent contact management, making mobile communication more secure, personalized, and efficient.

[0022] As according to the present invention, the Blockchain-Backed Security Module (108) is a privacy-enhancing and tamper-proof security mechanism designed to protect contact information, regulate app access, and provide secure contact management in mobile devices. This module leverages blockchain technology to create an immutable access log, ensuring that all interactions with the user's contact list — whether by installed applications, system features, or external services are securely recorded and verifiable. It enables real-time monitoring of app permissions, allowing users to track which applications have accessed their contact data and dynamically revoke access through smart contract-based authentication. The decentralized architecture of the module ensures that unauthorized modifications, data breaches, or third-party exploitation of contact information are prevented, significantly enhancing privacy protection. Additionally, it works in conjunction with the Al-powered processing Unit (106) to enforce automated privacy rules, selective app access control, and contact group-based permissions, ensuring that temporary or restricted contacts cannot interact with unauthorized applications. By integrating tamper-proof security, transparent access control, and decentralized privacy enforcement, the Blockchain-Backed Security Module (108) significantly improves data integrity, user control, and protection against unauthorized contact list exploitation, making mobile communication safer and more secure.

[0023] As according to the present invention, the Dynamic Privacy Control Interface (110), as per the present invention, is an interactive user interface and control mechanism that allows users to configure, monitor, and manage privacy settings for their contacts, app access permissions, and communication preferences in real-time. This interface enables users to assign contact groups (e.g., Family, Professional, Temporary) with specific privacy rules, ensuring that only authorized contacts can access certain applications or view user activity (e.g., WhatsApp status visibility). It provides granular control over Silent Mode, Do Not Disturb (DND), and call filtering settings, allowing users to selectively mute, block, or prioritize communication based on contextual requirements. The interface dynamically integrates with the Al-Powered Processing Unit (106) and Blockchain- Backed Security Module (108) to provide real-time alerts and access logs, enabling users to track and revoke unauthorized app access or suspicious interactions with their contact list. Additionally, it supports custom automation rules, such as auto-deletion of temporary contacts and intelligent recommendations for outdated contact cleanup, improving both privacy protection and contact organization. By offering adaptive, user-friendly, and Al-driven privacy management, the Dynamic Privacy Control Interface (110) ensures enhanced security, seamless customization, and a more controlled communication experience for mobile users.

[0024] In FIG. 1, the Al-driven intelligent contact management module (102) serves as the core system component, responsible for categorizing, optimizing, and managing contact information in real time. It communicates with the Central Contact Optimization Server (104), which synchronizes contact preferences across multiple devices and ensures consistent contact grouping, temporary contact handling, and privacy enforcement. The Al-Powered Processing Unit (106) integrates with both modules to analyze contact usage patterns, predict deletions, automate group assignments, and configure Silent Mode, Do Not Disturb (DND), and call filtering dynamically. To enhance security, the Blockchain-Backed Security Module (108) records and monitors all contact list interactions, app permissions, and privacy settings using a tamper-proof decentralized ledger, preventing unauthorized access to user data. The Dynamic Privacy Control Interface (110) acts as the user’s central dashboard, allowing real-time configuration of privacy settings, app access permissions, and communication preferences while providing alerts and access logs from the Blockchain-Backed Security Module (108). These components work together in a seamless, automated, and Al-driven ecosystem, ensuring efficient contact management, enhanced privacy protection, intelligent call handling, and secure, adaptive mobile communication.

[0025] FIG. 2 is a block diagram illustrating the architecture of the Al-powered processing unit (106), configured for real-time contact usage analysis, adaptive contact grouping, blockchain- backed access control, and predictive contact retention management, in accordance with an embodiment of the present invention. The Al-powered processing unit (106), as depicted in conjunction with elements from FIG. 1, includes a processor (202), memory (204), sensor interfaces (206), communication module (208), and contact management system (210). It is connected to various contact analysis and privacy control modules, including the usage pattern recognition system (212), blockchain security module (214), and Al-based privacy enforcement system (216), enabling real-time contact classification, selective app access control, automated temporary contact expiration, and intelligent call filtering. The processor (202) executes machine learning algorithms stored in memory (204) to analyze contact retention trends, suggest optimal categorization, and implement user-defined privacy policies dynamically. The sensor interfaces (206) integrate with various smartphone applications and communication systems to track real-time contact interactions and optimize silent mode, Do Not Disturb (DND), and call-blocking settings. The communication module (208) ensures secure synchronization with the Central Contact Optimization Server (104) and allows users to manage contact preferences across multiple devices. The contact management system (210) automates contact organization, predictive deletions, and context-aware privacy adjustments, ensuring seamless, Al-driven, and privacy-focused contact management.

[0026] As according to the present invention, the Processor (202) is the computational unit of the Al-powered processing unit (106), responsible for executing machine learning algorithms, predictive analytics, and privacy enforcement mechanisms to optimize contact management, app access control, and communication preferences. It continuously monitors contact usage patterns, detecting frequently used, redundant, or obsolete contacts, and dynamically categorizes them into adaptive groups (e.g., Family, Professional, Temporary). The Processor (202) also enables real-time configuration of Silent Mode, Do Not Disturb (DND), and call filtering by applying these settings selectively to specific contact groups instead of the entire phone. Additionally, it integrates with the Blockchain-Backed Security Module (108) to maintain tamper-proof access logs, allowing users to monitor and revoke unauthorized app access to contacts dynamically. The Processor (202) facilitates automated deletion of temporary contacts, ensuring that short-term numbers are not permanently stored or exposed to third-party applications. Furthermore, it enables secure, loT-based contact synchronization across multiple devices, ensuring that users experience a seamless, privacy- enhanced, and Al-driven contact management system.

[0027] As according to the present invention, the Memory (204) acts as the primary storage unit within the Al-powered processing unit (106), responsible for storing contact data, machine learning models, privacy settings, and access control logs required for intelligent contact management. It retains contact usage history, adaptive group classifications, and predictive analytics data, allowing the system to continuously learn from user behavior and optimize contact retention or deletion accordingly. The Memory (204) also stores user-defined configurations for Silent Mode, Do Not Disturb (DND), call filtering, and selective app access, ensuring that these settings persist across multiple device sessions. Additionally, it works in conjunction with the Blockchain-Backed Security Module (108) to securely log app permissions, access attempts, and privacy enforcement actions, providing tamper-proof records for contact security. The Memory (204) enables efficient data retrieval for real-time decision-making, ensuring that the Processor (202) can execute privacy controls, Al-driven contact classification, and predictive deletions without delays. By supporting fast access, secure storage, and adaptive data handling, the Memory (204) ensures a seamless, privacy-enhanced, and automated contact management experience for users.

[0028] As according to the present invention, the Sensor Interfaces (206) act as a bridge between the Al-powered processing unit (106) and various smartphone applications, communication systems, and external sensors. These interfaces continuously monitor contact interactions, detect usage patterns, and track real-time changes in communication behavior, enabling the system to intelligently categorize contacts, automate temporary contact expiration, and optimize privacy settings dynamically. Additionally, the Sensor Interfaces (206) facilitate context-aware configuration of Silent Mode, Do Not Disturb (DND), and call filtering, ensuring that the system adapts contact-based settings in real-time based on environmental and user-specific triggers. By integrating with external applications and privacy modules, the Sensor Interfaces (206) enable seamless, Al-driven contact management and enhanced user privacy.

[0029] As according to the present invention, the Communication Module (208) facilitates secure and seamless data exchange between the Al-powered processing unit (106), the Central Contact Optimization Server (104), and external applications to ensure real-time synchronization, privacy enforcement, and adaptive contact management. It enables wireless and cloud-based communication, allowing users to access and update contact preferences across multiple devices while maintaining consistent privacy controls and app access restrictions. Additionally, the Communication Module (208) works in conjunction with the Blockchain-Backed Security Module (108) to log and regulate third-party app interactions with contact data, ensuring tamper-proofsecurity and real-time permission management. By supporting loT-based synchronization and AI- driven automation, the Communication Module (208) enhances contact privacy, accessibility, and intelligent communication handling across user devices.

[0030] As according to the present invention, the Contact Management System (210) acts as the core functional unit responsible for organizing, optimizing, and securing contact information through Al-driven automation. It categorizes contacts into adaptive groups (e.g., Family, Professional, Temporary), automates the deletion of unused or temporary contacts, and ensures selective app access control to protect user privacy. The system also integrates with the Al-powered processing unit (106) to analyze contact usage patterns, suggest optimal retention or deletion actions, and configure Silent Mode, Do Not Disturb (DND), and call filtering based on predefined rules. Additionally, it works in conjunction with the Blockchain-Backed Security Module (108) to prevent unauthorized access to contact data and maintain tamper-proof access logs. By enabling predictive contact retention, privacy-focused automation, and real-time adaptability, the Contact Management System (210) enhances communication efficiency, security, and user experience in mobile devices.

[0031] As according to the present invention, the Pattern Recognition System (212) is an Al-driven analytical module that continuously monitors and analyzes contact usage patterns to optimize contact organization, privacy settings, and communication preferences. It detects frequently used, rarely contacted, or redundant entries, enabling intelligent categorization and predictive deletion of outdated contacts. This system also identifies behavioral trends, such as call frequency, message exchanges, and app interactions, to suggest adaptive contact grouping and automated privacy configurations. Integrated with the Al-powered processing unit (106), it enhances real-time decision-making for Silent Mode, Do Not Disturb (DND), and selective call filtering, ensuring that user-defined preferences are applied dynamically. By leveraging machine learning algorithms, the Pattern Recognition System (212) plays a crucial role in making contact management smarter, automated, and privacy-focused.

[0032] As according to the present invention, the Blockchain Security Module (214) is a tamperproof security mechanism designed to safeguard contact data, regulate app access, and ensure privacy protection in mobile devices. By leveraging decentralized blockchain technology, this module records and verifies all interactions with the user's contact list, ensuring that unauthorized modifications, third-party access, and data breaches are prevented. It maintains immutable accesslogs, allowing users to monitor app permissions, revoke access dynamically, and track contact- related activities in real time. Integrated with the Al-powered processing unit (106), it enhances contact privacy by enforcing selective app access control and restricting temporary contacts from unauthorized usage. By ensuring secure, verifiable, and transparent access management, the Blockchain Security Module (214) significantly strengthens data integrity, user control, and privacy protection in intelligent contact management systems.

[0033] As according to the present invention, the AI-Based Privacy Enforcement System (216) is an intelligent security module that ensures real-time monitoring, enforcement, and dynamic control of contact-related privacy settings in mobile devices. Using machine learning algorithms, it analyzes user behavior, contact interactions, and app access requests to automatically restrict unauthorized access, configure selective app permissions, and enforce privacy rules based on adaptive contact grouping. Integrated with the Blockchain Security Module (214), it maintains tamper-proof logs of contact access and modifications, allowing users to track, manage, and revoke permissions dynamically. Additionally, it enhances context-aware privacy settings, such as automated Silent Mode, Do Not Disturb (DND), and selective call filtering, ensuring that users receive only relevant communications while protecting their sensitive contact data. By leveraging Al-driven automation and blockchain-backed security, the AI-Based Privacy Enforcement System (216) significantly enhances data protection, communication control, and user privacy in intelligent contact management systems.

[0034] In FIG. 2, the Al-powered processing unit (106) serves as the central control system, orchestrating various components to enable intelligent contact management, privacy enforcement, and communication optimization. The Processor (202) executes machine learning algorithms stored in Memory (204) to analyze contact usage patterns, predict deletions, and manage adaptive contact grouping. The Sensor Interfaces (206) continuously monitor real-time contact interactions, app access requests, and communication behavior, feeding this data to the Pattern Recognition System (212), which detects behavioral trends and categorizes contacts accordingly. The Communication Module (208) ensures seamless synchronization with the Central Contact Optimization Server (104), allowing users to manage their contact preferences across multiple devices. The Contact Management System (210) automates contact organization, privacy rule enforcement, and temporary contact deletion, integrating closely with the AI-Based Privacy Enforcement System (216) to dynamically restrict app access, configure selective silent mode, and enhance privacy settings based on user-defined rules. The Blockchain Security Module (214) records all contact-related interactions and app permissions in a tamper-proof ledger, ensuring secure access control and real-time revocation capabilities. Together, these components create an Al-driven, privacy- focused, and adaptive contact management ecosystem, ensuring secure, optimized, and user- friendly communication experiences across mobile devices.

[0035] In an exemplary operation, a system to intelligently manage mobile device contacts, enhance privacy, and optimize communication preferences is disclosed. The system comprises an AI- powered processing unit (106) that analyzes contact usage patterns, categorizes contacts into adaptive groups, and automates temporary contact deletion. The system comprises a Central Contact Optimization Server (104) that ensures real-time synchronization of contact preferences across multiple devices and dynamic configuration of Silent Mode, Do Not Disturb (DND), and call filtering. In an embodiment, the system integrates a Blockchain Security Module (214) to maintain tamper-proof access logs, regulate app permissions, and provide real-time privacy enforcement. In an embodiment, the Al -Based Privacy Enforcement System (216) dynamically restricts unauthorized access to contact data, ensures app-specific privacy settings, and enforces user-defined security rules. In an embodiment, the Pattern Recognition System (212) detects frequently used, rarely contacted, or redundant entries to facilitate predictive contact retention analysis and intelligent deletion suggestions. In an embodiment, the Contact Management System (210) automates contact organization, privacy rule enforcement, and temporary contact expiration, working in conjunction with the Processor (202) and Memory (204) to execute machine learning models, store user preferences, and enhance real-time decision-making. The Communication Module (208) facilitates secure data exchange with the Central Contact Optimization Server (104), ensuring seamless loT-based synchronization of contact settings. Through Al-driven automation, blockchain-backed security, and predictive analytics, this system ensures an adaptive, privacy- enhanced, and user-friendly contact management experience.

[0036] In an embodiment, the Processor (202) is configured to analyze contact usage patterns in real-time, detecting frequently used, redundant, or obsolete contacts and categorizing them into adaptive groups such as Family, Professional, and Temporary Contacts. In an embodiment, the Processor (202) is configured to predict and automate contact deletions for temporary or inactive contacts based on predefined retention rules and Al-based behavioral analysis. In an embodiment, the Processor (202) is configured to enforce selective app access control, ensuring that only authorized contact groups interact with specific applications, thereby enhancing privacy and reducing unnecessary exposure of contact data. In an embodiment, the Processor (202) is configuredto dynamically configure Silent Mode, Do Not Disturb (DND), and call filtering settings, allowing users to apply communication restrictions based on contact groups instead of universal settings. In an embodiment, the Processor (202) is configured to integrate with the Blockchain Security Module (214) to log all contact-related interactions in a tamper-proof ledger, allowing real-time monitoring and revocation of third-party app permissions. In an embodiment, the Processor (202) is configured to work with the AI-Based Privacy Enforcement System (216) to detect unauthorized access attempts, restrict sensitive contact exposure, and enhance overall contact security. In an embodiment, the Processor (202) is configured to enable loT-based synchronization, ensuring that contact preferences, privacy rules, and communication settings are seamlessly maintained across multiple devices. Through these advanced functionalities, the Processor (202) enhances automation, privacy, and intelligent contact management in mobile devices.

[0037] In an embodiment, the system enables both manual and Al-driven contact configuration for efficient contact management. While users can manually assign contacts to predefined groups such as Family, Professional, and Temporary Contacts, this process can be tedious and requires continuous user intervention. To overcome this limitation, the system comprises an Al-powered processing unit configured to analyze contact usage patterns, interaction frequency, and contextual relevance to dynamically categorize contacts into appropriate groups. The Al-driven approach detects frequently used, redundant, or inactive contacts, ensuring automatic updates and real-time optimization of the contact list. Furthermore, the system adapts to changing user behavior, enabling intelligent reclassification of contacts without manual effort. By integrating machine learning algorithms, the system ensures that privacy settings, app access permissions, and communication preferences are applied contextually based on contact group classification, enhancing efficiency, usability, and user privacy while reducing the need for manual reconfiguration.

[0038] In another embodiment, the present invention provides an Al-driven system for intelligent call prioritization and spam filtering, enhancing contact-based communication efficiency and security. The system dynamically identifies important contacts, assigns priority levels, and filters out spam or low-priority calls based on real-time Al analysis. The Al-powered processing unit (106) evaluates call frequency, message exchanges, and past interactions to determine whether an incoming call should be allowed, silenced, or blocked automatically. The Pattern Recognition System (212) detects suspicious or unknown numbers and cross-references them with a global spam database to prevent unwanted calls from reaching the user. The Contact Management System (210) integrates with the Silent Mode and Do Not Disturb (DND) configurations, allowing users to enableselective call filtering based on time, location, or predefined scenarios (e.g., silencing work- related calls at night while keeping emergency contacts active). Additionally, the Blockchain Security Module (214) ensures that all call access logs and user-defined preferences are securely stored, preventing unauthorized modifications. The AI-Based Privacy Enforcement System (216) further monitors third-party apps that request call or contact list access, ensuring that privacy-sensitive data is not exposed without user consent. Through real-time Al-driven prioritization, automated spam detection, and blockchain-backed security, this embodiment significantly improves user privacy, reduces interruptions, and enhances the efficiency of mobile communication management.

[0039] In another embodiment, the present invention provides an Al-driven system for intelligent emergency contact management and real-time situational awareness, enhancing user safety and communication efficiency in critical situations. The system dynamically identifies emergency contacts, prioritizes urgent communications, and automatically adjusts privacy and accessibility settings based on real-time context and user activity. The Al-powered processing unit (106) continuously monitors location data, motion patterns, and device activity to detect emergency scenarios, such as accidents, health-related incidents, or security threats. The Pattern Recognition System (212) analyzes call and message patterns to ensure that high-priority contacts (e.g., family members, medical professionals, emergency services) remain accessible even when Silent Mode or Do Not Disturb (DND) is enabled. The Contact Management System (210) dynamically prioritizes emergency calls and messages, ensuring that critical alerts bypass restricted settings and reach the user immediately. Additionally, the Blockchain Security Module (214) securely logs emergency contact interactions, ensuring tamper-proof records of distress signals or SOS notifications. The AI- based Privacy Enforcement System (216) automatically grants temporary access to emergency contacts for location sharing, health status updates, or real-time assistance while preventing unauthorized access to non-essential data. Through context-aware Al decision-making, real-time contact prioritization, and blockchain-backed security, this embodiment ensures that users remain connected to essential contacts while maintaining privacy and minimizing disruptions in nonemergency situations.

[0040] Let us consider a practical scenario to illustrate the workings of the present invention. Consider a user managing multiple contact groups, including Family, Professional, and Temporary Contacts, on their smartphone. The user frequently interacts with family members and colleagues but occasionally saves temporary numbers, such as delivery agents, customer service representatives, or event- specific contacts. Without intelligent contact management, thesetemporary contacts remain in the phone indefinitely, cluttering the contact list and potentially exposing the user’s information to third-party applications. Using the Al-powered processing unit (106), the system automatically analyzes contact usage, detects inactive or redundant numbers, and classifies them into appropriate groups. If a temporary contact has not been used for a predefined duration, the system prompts the user to delete it or automatically removes it based on user settings. Meanwhile, the user enables Selective Silent Mode to mute professional contacts during off-hours while keeping emergency contacts from the Family group active. The Blockchain Security Module (214) logs all access attempts by third-party apps and allows the user to review and revoke unnecessary permissions through the Dynamic Privacy Control Interface (110). Additionally, if an unknown number repeatedly calls, the Pattern Recognition System (212) identifies it as potential spam, and the system automatically blocks or silences it based on Al-driven analysis. Through realtime Al-based decision-making, selective access control, and automated privacy enforcement, the present invention enhances contact management efficiency, prevents data clutter, optimizes communication preferences, and strengthens user privacy.

[0041] FIG. 3 is a flowchart that illustrates a method for Al-driven intelligent contact management, privacy enforcement, and dynamic communication control, in accordance with an embodiment of the present disclosure. The method begins in a Start step (302) and proceeds to a Contact Analysis step (304), where the Al-powered processing unit (106) analyzes contact usage patterns, identifies frequently used, inactive, or redundant contacts, and classifies them into adaptive groups such as Family, Professional, and Temporary Contacts. At Step 306, the Pattern Recognition System (212) detects behavioral trends and suggests automated updates or deletions for outdated or temporary contacts. At Step 308, the system enforces privacy rules by restricting app access to specific contact groups, ensuring that third-party applications do not access unintended contacts. At Step 310, the Blockchain Security Module (214) logs contact interactions and app permissions, allowing users to monitor access and revoke unauthorized requests through the Dynamic Privacy Control Interface (110). At Step 312, the system configures Selective Silent Mode, Do Not Disturb (DND), and call filtering settings dynamically, enabling users to prioritize important contacts while muting unnecessary disturbances. At Step 314, the Contact Management System (210) synchronizes settings across multiple devices using loT-based communication via the Central Contact Optimization Server (104). At Step 316, the Al -Based Privacy Enforcement System (216) continuously monitors new contacts, unauthorized access attempts, and behavioral patterns to maintain adaptive privacy settings. The method concludes at Step 318, ensuring that all privacypreferences, app permissions, and contact management rules remain updated, automated, and user- driven, thereby enhancing mobile security, communication efficiency, and overall user experience.

[0042] FIG. 4 is a flowchart that illustrates how the Processor (202) is configured to execute AI- driven intelligent contact management, privacy enforcement, and dynamic communication control, in accordance with an embodiment of the present invention. The method begins in a Start step (402) and proceeds to a Contact Analysis step (404), where the processor monitors contact interactions, identifies frequently used, inactive, or redundant contacts, and dynamically categorizes them into adaptive groups such as Family, Professional, and Temporary Contacts. At Step 406, the processor applies machine learning algorithms to detect temporary contacts and suggests automated deletion based on predefined retention rules. At Step 408, the processor executes privacy enforcement mechanisms by selectively granting or restricting third-party app access to specific contact groups, ensuring that sensitive contacts are protected from unauthorized exposure. At Step 410, the Blockchain Security Module (214) logs all contact access attempts, app permissions, and privacy modifications, creating an immutable and tamper-proof access record for user review. At Step 412, the processor dynamically configures Silent Mode, Do Not Disturb (DND), and call filtering settings, ensuring that only priority contacts can bypass restrictions while blocking spam or low- priority calls. At Step 414, the processor communicates with the Central Contact Optimization Server (104) to synchronize contact preferences, privacy settings, and communication rules across multiple devices. At Step 416, the processor integrates with the Al-based privacy enforcement system (216) to detect unauthorized access attempts, enforce real-time privacy adjustments, and adapt security protocols based on usage patterns. At Step 418, the system updates all privacy rules, app permissions, and contact management settings dynamically, ensuring a secure, adaptive, and automated mobile communication experience. Through Al-driven automation, blockchain-backed security, and predictive analytics, the Processor (202) optimizes user privacy, enhances data security, and streamlines intelligent contact management in mobile devices.

[0043] The present disclosure offers several technical advantages over conventional contact management systems by integrating Al-driven automation, blockchain-backed security, and dynamic privacy enforcement mechanisms to optimize contact organization, communication efficiency, and data privacy. Firstly, its integration of multiple sensor interfaces (206) and AI- powered pattern recognition system (212) enables real-time contact usage analysis, adaptive grouping, and predictive retention management, ensuring that temporary or obsolete contacts are automatically identified and removed without manual intervention. This enhanced Al-basedautomation minimizes data clutter, prevents unnecessary app access to sensitive contacts, and optimizes mobile communication settings dynamically. Additionally, the use of the Blockchain Security Module (214) ensures tamper-proof access logs, secure permission control, and dynamic revocation of third-party app access, preventing unauthorized data exposure and enhancing user privacy. The system further incorporates Selective Silent Mode, Al-driven Do Not Disturb (DND), and intelligent call filtering, allowing context-aware customization of communication settings based on user-defined preferences and behavioral insights. Moreover, the AI-Based Privacy Enforcement System (216) continuously monitors app requests, restricts contact access dynamically, and ensures compliance with real-time security protocols, significantly enhancing privacy protection. The system's seamless loT-based synchronization with the Central Contact Optimization Server (104) ensures that contact preferences and privacy rules remain consistent across multiple devices, improving user experience and accessibility. By integrating predictive analytics, machine learning, and decentralized security mechanisms, the present invention overcomes the limitations of conventional contact management systems, offering a next-generation, intelligent, and adaptive solution for secure, efficient, and automated contact handling.

[0044] The present disclosure provides a concrete and tangible solution to a significant technical problem in the field of intelligent contact management, privacy enforcement, and communication optimization for mobile devices. Traditional contact management systems lack automation, security, and contextual adaptability, leading to cluttered contact lists, privacy vulnerabilities, and inefficient communication control mechanisms. The present disclosure offers specific technical features and functionalities that overcome these limitations by integrating Al-driven contact categorization, predictive retention analysis, and blockchain-backed security mechanisms. The system leverages an Al-powered processing unit (106) to analyze contact usage patterns, classify contacts into adaptive groups, and automate the deletion of temporary or redundant entries. Additionally, the Pattern Recognition System (212) dynamically detects behavioral trends to optimize contact retention, prevent unnecessary data accumulation, and enhance efficiency. The Blockchain Security Module (214) provides tamper-proof access logs, ensuring secure monitoring, regulation, and revocation of third-party app permissions to prevent unauthorized access to user data. The system also features Selective Silent Mode, Al-enhanced Do Not Disturb (DND), and intelligent call filtering, allowing customized privacy settings and communication control based on user-defined preferences and contextual triggers. Furthermore, the AI-Based Privacy Enforcement System (216) ensures realtime protection by monitoring app requests, restricting unauthorized contact access, anddynamically adapting privacy settings. The system's loT-based synchronization with the Central Contact Optimization Server (104) guarantees that contact preferences, privacy rules, and security settings remain consistent across multiple devices, enhancing usability and accessibility. By combining machine learning, predictive analytics, decentralized security, and Al-driven automation, the present invention addresses the critical inefficiencies of conventional contact management systems, providing a next-generation, intelligent, and privacy-focused solution for mobile communication.

Claims

We Claim:

1. A system for intelligent contact management, privacy control, and dynamic communication optimization, the system comprising: an Al-powered processing unit, configured to: analyze contact usage patterns and categorize contacts into adaptive groups such as family, professional, and temporary contacts; and predict and automate the deletion of unused or temporary contacts based on predefined retention rules and user behavior analysis and dynamically configure Silent Mode, Do Not Disturb (DND), and call filtering settings based on contact groups instead of universal or individual contact settings; a pattern recognition system, configured to: detect frequently used, rarely contacted, and redundant entries; suggest optimal contact retention or deletion based on historical interaction trends; and identify and flag suspicious or unknown numbers for potential spam filtering; a contact management system, configured to: automate contact organization, privacy rule enforcement, and temporary contact expiration; restrict access to certain applications based on predefined user preferences for contact groups; and synchronize contact settings across multiple devices via loT-based communication; a blockchain security module, configured to: store tamper-proof access logs of contact list modifications and app interactions; provide real-time permission management for monitoring and revoking third-party app access; and prevent unauthorized access to contact data through decentralized authentication; an Al-based privacy enforcement system, configured to: monitor app requests for contact list access and restrict unauthorized interactions dynamically; provide real-time alerts and allow users to modify privacy settings as required; and integrate with the Blockchain Security Module to maintain an immutable security record; a communication module, configured to:enable secure data exchange between the Al-powered processing unit, contact management system, and external applications; and ensure seamless synchronization of contact preferences and privacy settings across multiple devices.

2. The system of claim 1, wherein, the Al-powered processing unit automates contact categorization and deletion based on configurable retention policies, and the pattern recognition system identifies spam numbers and automatically silences or blocks unwanted calls.

3. The system of claim 1, wherein the blockchain security Module ensures that all contact interactions and app permissions are securely stored and immutable.

4. The system of claim 1, wherein the contact management system allows selective contact-based configurations for silent mode and Do Not Disturb (DND), ensuring that only certain contact groups can bypass restrictions.

5. The system of claim 1, wherein, the communication module enables encrypted data transmission, preventing unauthorized modifications to contact settings.

6. A method for intelligent contact management, privacy control, and dynamic communication optimization, the method comprising: analyzing contact usage patterns using an Al-powered processing unit to categorize contacts into adaptive groups; detecting and removing redundant or obsolete contacts based on predefined user settings and machine learning models. configuring and enforcing privacy rules dynamically, including restricting certain contact groups from accessing specific applications; generating real-time privacy alerts through the Al-based privacy enforcement system to prevent unauthorized contact list access; logging all contact interactions in a tamper-proof blockchain ledger and allowing users to monitor and revoke third-party app permissions; synchronizing contact settings across multiple devices via an loT-based communication module; anddynamically adapting silent mode, Do Not Disturb (DND), and call filtering configurations based on contact group classification and contextual user preferences.

7. The method of claim 6, wherein, the Al-powered processing unit detects temporary contacts and removes them automatically after a set duration, and the Al-based privacy enforcement system monitors and restricts third-party apps from accessing sensitive contact data.

8. The method of claim 6, wherein the blockchain security module maintains decentralized security logs, allowing real-time monitoring and permission revocation.

9. The method of claim 6, wherein, the Al-based privacy enforcement system grants temporary access to emergency contacts during distress situations while restricting unnecessary data exposure.

10. The method of claim 6, wherein the contact management system automatically identifies and notifies users about long-unused but important contacts for proactive relationship maintenance.

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