CONTROL MECHANISMS FOR ELECTRONIC DEVICES WITH ARTIFICIAL INTELLIGENCE CAPABILITIES

Abstract

ABSTRACT Control Mechanisms for Electronic Devices with Artificial Intelligence Capabilities The present disclosure introduces a control mechanism for electronic devices with artificial intelligence capabilities, designed to enhance operational efficiency, adaptability, and user interaction. The system includes data acquisition unit 102 to collect real-time data from embedded sensors, and data processing module 104 to analyze the data using machine learning algorithms. Decision-making engine 106 formulates control strategies, while user interaction interface 108 provides real-time feedback and captures user preferences. The other key components are connectivity module 110, adaptive learning algorithm 112 multi-sensor integration 114, edge computing capability 116, cloud connectivity and data synchronization 118, intelligent resource management module 120, self-diagnostics and maintenance alerts 122, interoperability framework 124, privacy and security features 126, dynamic user feedback loop 128, context-aware operation 130, energy harvesting capabilities 132, multi-modal interaction interface 134. Reference Fig 1

Specification

Description:CONTROL MECHANISMS FOR ELECTRONIC DEVICES WITH ARTIFICIAL INTELLIGENCE CAPABILITIES
TECHNICAL FIELD
[0001] The present innovation relates to AI-driven control mechanisms for enhancing the efficiency, adaptability, and user interaction of electronic devices across various applications.

BACKGROUND

[0002] The growing integration of electronic devices into daily life, from smart home appliances to industrial machinery, has led to a need for advanced control mechanisms that can optimize performance, improve user interaction, and enhance adaptability. Traditional control systems often rely on predefined algorithms and manual user input, which limits their flexibility in responding to changing environmental conditions or user preferences. This creates inefficiencies, particularly in systems that require continuous adjustment, such as smart thermostats, industrial automation systems, or healthcare devices.

[0003] Existing solutions offer some improvements, such as programmable controls or basic automation features, but these often require significant manual setup and lack real-time adaptability. Moreover, many devices lack integration across platforms, resulting in siloed systems that miss opportunities for optimized performance through data sharing. These options do not adequately utilize modern advancements in artificial intelligence (AI), limiting their potential to offer autonomous, intelligent control and adaptive decision-making based on user behavior and environmental factors.


[0004] The present invention addresses these shortcomings by incorporating AI-driven control mechanisms, which differentiate it from traditional systems by using machine learning algorithms to continuously adapt to real-time data. This enables devices to learn from historical data and user interactions, allowing for autonomous adjustments without requiring constant user input. The novelty of the invention lies in its ability to integrate data from multiple sensors and leverage predictive analytics to anticipate future needs, ensuring optimal device performance. It also incorporates edge computing for faster, localized data processing and decision-making, while offering features like user-centric personalization, energy optimization, and multi-device connectivity. This invention overcomes the limitations of traditional systems by enhancing adaptability, improving resource management, and providing a more seamless and intelligent user experience across a wide range of electronic devices.

OBJECTS OF THE INVENTION

[0005] The primary object of the invention is to enhance the operational efficiency of electronic devices by incorporating AI-driven control mechanisms that adapt to real-time data.

[0006] Another object of the invention is to improve user interaction by enabling electronic devices to autonomously adjust based on user behavior and preferences.


[0007] Another object of the invention is to optimize resource management in electronic devices, such as energy consumption and operational performance, through intelligent decision-making algorithms.

[0008] Another object of the invention is to offer seamless integration with other smart devices and cloud platforms, allowing for interconnected data sharing and collaborative operations.
[0009] Another object of the invention is to reduce the need for manual user input by enabling devices to operate autonomously and intelligently, enhancing overall usability.

[00010] Another object of the invention is to increase the adaptability of electronic devices, ensuring they remain efficient under varying environmental conditions and operational requirements.

[00011] Another object of the invention is to incorporate predictive analytics that allow devices to anticipate user needs or operational changes, providing proactive adjustments for optimal performance.

[00012] Another object of the invention is to enhance device security and privacy by incorporating robust data encryption and user authentication protocols, addressing concerns about cybersecurity in smart devices.

[00013] Another object of the invention is to provide a scalable and versatile solution that can be applied across a wide range of fields, including smart homes, industrial automation, healthcare, and consumer electronics.

[00014] Another object of the invention is to promote sustainability by enabling devices to optimize energy use, reducing waste, and aligning with responsible consumption and production practices.

SUMMARY OF THE INVENTION

[00015] In accordance with the different aspects of the present invention, control mechanisms for electronic devices with artificial intelligence capabilities is presented. It enhance the efficiency, adaptability, and user interaction of electronic devices across various applications. By leveraging machine learning and real-time data processing, the system autonomously adjusts device operations based on user behavior and environmental conditions. It optimizes resource management, reduces the need for manual input, and integrates seamlessly with other smart devices. The invention also incorporates advanced security features and promotes sustainability by optimizing energy consumption. It is versatile and scalable, applicable to industries like smart homes, healthcare, and industrial automation.

[00016] Additional aspects, advantages, features and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments constructed in conjunction with the appended claims that follow.

[00017] It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.

BRIEF DESCRIPTION OF DRAWINGS
[00018] The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.

[00019] Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:

[00020] FIG. 1 is component wise drawing for control mechanisms for electronic devices with artificial intelligence capabilities.

[00021] FIG 2 is working methodology of control mechanisms for electronic devices with artificial intelligence capabilities.

DETAILED DESCRIPTION

[00022] The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognise that other embodiments for carrying out or practising the present disclosure are also possible.

[00023] The description set forth below in connection with the appended drawings is intended as a description of certain embodiments of control mechanisms for electronic devices with artificial intelligence capabilities and is not intended to represent the only forms that may be developed or utilised. The description sets forth the various structures and/or functions in connection with the illustrated embodiments; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimised to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.

[00024] While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.

[00025] The terms "comprises", "comprising", "include(s)", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, or system that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system. In other words, one or more elements in a system or apparatus preceded by "comprises... a" does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.

[00026] In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings and which are shown by way of illustration-specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.

[00027] The present disclosure will be described herein below with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.

[00028] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 is disclosed, in accordance with one embodiment of the present invention. It comprises of data acquisition unit 102, data processing module 104, decision-making engine 106, user interaction interface 108, connectivity module 110, adaptive learning algorithm 112, multi-sensor integration 114, edge computing capability 116, cloud connectivity and data synchronization 118, intelligent resource management module 120, self-diagnostics and maintenance alerts 122, interoperability framework 124, privacy and security features 126, dynamic user feedback loop 128, context-aware operation 130, energy harvesting capabilities 132, multi-modal interaction interface 134.

[00029] Referring to Fig. 1, the present disclosure provides details of control mechanisms for electronic devices with artificial intelligence capabilities 100. It is a system designed to enhance device efficiency, adaptability, and user interaction using machine learning and real-time data processing. It enables devices to autonomously adjust their operations based on user preferences and environmental conditions. In one of the embodiments, the control mechanism is provided with key components such as data acquisition unit 102, data processing module 104, and decision-making engine 106, which facilitate real-time data collection and intelligent decision-making. The system also features user interaction interface 108 for seamless communication and connectivity module 110 for device integration with other systems. Additional components such as adaptive learning algorithm 112 and intelligent resource management module 120 enable optimization of energy use and device performance.

[00030] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with data acquisition unit 102, which collects real-time data from sensors embedded in the device, such as temperature, humidity, and motion. This data forms the foundation for all decision-making processes. The data acquisition unit 102 works in close collaboration with data processing module 104, ensuring that the system has continuous and accurate input to analyze. This unit is essential for real-time monitoring and adapting the device's functionality based on environmental changes.

[00031] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with data processing module 104, which utilizes machine learning algorithms to analyze the data collected by data acquisition unit 102. It processes real-time data to identify patterns and trends, enabling the system to make intelligent decisions. The data processing module 104 is key to the overall system's functionality, as it feeds insights to the decision-making engine 106 for formulating control strategies. This component ensures that the device can adapt to changing conditions and optimize performance autonomously.

[00032] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with decision-making engine 106, which uses insights from data processing module 104 to formulate autonomous control strategies. It plays a central role in optimizing the operation of the device without requiring constant user intervention. The decision-making engine 106 communicates with both user interaction interface 108 and intelligent resource management module 120, ensuring that the device not only operates efficiently but also adapts to user preferences and environmental factors.

[00033] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with user interaction interface 108, which facilitates communication between the user and the device. This interface allows users to provide manual inputs and receive real-time feedback on device performance. The user interaction interface 108 works closely with decision-making engine 106, capturing user preferences and feeding them into the system's control algorithms. This integration ensures that the device adapts to user behaviors and preferences while maintaining optimal performance.

[00034] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with connectivity module 110, which enables the device to communicate with other smart devices and cloud platforms. It allows the system to share data and collaborate with other interconnected devices, improving overall efficiency. The connectivity module 110 interacts with the data acquisition unit 102 and cloud connectivity and data synchronization 118 to ensure seamless data transfer and synchronization across multiple devices, allowing for real-time remote monitoring and control.

[00035] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with adaptive learning algorithm 112, which refines the device's decision-making capabilities by analyzing historical and real-time data. This algorithm continuously improves the performance of the system by learning from user interactions and environmental changes. The adaptive learning algorithm 112 works in conjunction with the data processing module 104 and decision-making engine 106, enabling the system to adapt autonomously to varying conditions, ensuring optimal device functionality over time.

[00036] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with multi-sensor integration 114, which collects comprehensive data from various sensors such as temperature, humidity, and motion. By integrating multiple sources of data, the system gains a holistic view of its operating environment. The multi-sensor integration 114 feeds data into the data acquisition unit 102 and data processing module 104, ensuring that the device receives accurate and multi-faceted information for better decision-making and adaptability.

[00037] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with edge computing capability 116, which processes data locally on the device rather than relying solely on cloud-based systems. This reduces latency and ensures faster decision-making, especially for time-sensitive operations. The edge computing capability 116 works closely with data processing module 104 and decision-making engine 106, allowing the system to make real-time adjustments based on immediate environmental inputs.
[00038] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with cloud connectivity and data synchronization 118, which allows the device to synchronize data with cloud platforms and other devices. This feature enables remote monitoring, control, and data sharing across a network of smart devices. The cloud connectivity and data synchronization 118 works in conjunction with the connectivity module 110 and intelligent resource management module 120, ensuring that the system remains updated and responsive to broader network inputs.

[00039] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with intelligent resource management module 120, which optimizes energy use and operational efficiency. This module analyzes real-time data and adjusts the device's performance to reduce energy consumption while maintaining optimal operation. The intelligent resource management module 120 interacts with decision-making engine 106 and adaptive learning algorithm 112, ensuring that the device's resource usage is continuously optimized based on usage patterns and environmental conditions.

[00040] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with self-diagnostics and maintenance alerts 122, which monitors the health and performance of the device. It detects potential issues before they escalate into critical failures, alerting users for timely maintenance. The self-diagnostics and maintenance alerts 122 works in conjunction with data acquisition unit 102 and decision-making engine 106, enabling proactive maintenance and reducing downtime through predictive insights.

[00041] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with interoperability framework 124, which ensures compatibility and seamless communication with various smart home ecosystems, industrial protocols, and external systems. This framework allows the device to integrate smoothly into a wide range of environments. The interoperability framework 124 collaborates with connectivity module 110 and cloud connectivity and data synchronization 118, enabling devices to share data and communicate effectively with other systems.


[00042] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with privacy and security features 126, which incorporate advanced data encryption and user authentication protocols to safeguard sensitive information. These features protect the device and its data from potential cybersecurity threats. The privacy and security features 126 interact with connectivity module 110 and cloud connectivity and data synchronization 118, ensuring secure communication within the device network while maintaining data privacy for users.

[00043] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with dynamic user feedback loop 128, which continuously collects user inputs and device performance data to improve system functionality in real time. This feedback is integrated into the decision-making engine 106 and adaptive learning algorithm 112, allowing the device to adjust its operations based on evolving user preferences and behavior. This enhances the overall user experience and device adaptability.

[00044] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with context-aware operation 130, which adjusts the device's behavior based on situational data such as time of day, user location, and current activity. This feature ensures that the device provides an optimal user experience by adapting its functionality according to the context. The context-aware operation 130 works in conjunction with data acquisition unit 102 and decision-making engine 106, allowing the system to make decisions that are highly relevant to the immediate environment.

[00045] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with energy harvesting capabilities 132, which enable the device to power itself using renewable energy sources such as solar panels or kinetic energy. This sustainable approach reduces reliance on traditional power sources, enhancing the eco-friendliness of the system. The energy harvesting capabilities 132 integrate with intelligent resource management module 120, optimizing the use of harvested energy and further promoting energy efficiency.

[00046] Referring to Fig. 1, control mechanisms for electronic devices with artificial intelligence capabilities 100 are provided with multi-modal interaction interface 134, which allows users to interact with the device through various input methods, including voice commands, touch, and gestures. This versatility accommodates different user preferences and enhances accessibility. The multi-modal interaction interface 134 works in conjunction with user interaction interface 108 and decision-making engine 106, enabling seamless and user-friendly operation of the device across different input modalities.

[00047] Referring to Fig 2, there is illustrated method 200 for control mechanisms for electronic devices with artificial intelligence capabilities 100. The method comprises:

At step 202, method 200 includes data acquisition unit 102 collecting real-time data from embedded sensors to monitor the device's operational environment;

At step 204, method 200 includes data processing module 104 analyzing the collected data using machine learning algorithms and forwarding insights to decision-making engine 106;

At step 206, method 200 includes decision-making engine 106 formulating control strategies based on the analyzed data and adjusting the device's performance accordingly;

At step 208, method 200 includes user interaction interface 108 providing feedback to the user and integrating manual adjustments into the system's control algorithms;

At step 210, method 200 includes connectivity module 110 facilitating communication with other smart devices and platforms for data sharing and synchronization;

At step 212, method 200 includes adaptive learning algorithm 112 refining control strategies based on historical data and real-time user interactions;

At step 214, method 200 includes intelligent resource management module 120 optimizing energy consumption and performance based on real-time and predictive data;

At step 216, method 200 includes self-diagnostics and maintenance alerts 122 monitoring device health and alerting the user for preventive maintenance;

At step 218, method 200 includes interoperability framework 124 ensuring compatibility and seamless communication with external systems through connectivity module 110;

At step 220, method 200 includes privacy and security features 126 encrypting data and securing communications within the device network;

At step 222, method 200 includes dynamic user feedback loop 128 continuously collecting and incorporating user input to refine system performance;

At step 224, method 200 includes context-aware operation 130 adjusting device behavior based on situational data like time of day or user location;

At step 226, method 200 includes energy harvesting capabilities 132 generating power from renewable sources to reduce reliance on external power;

At step 228, method 200 includes multi-modal interaction interface 134 enabling user control through voice, touch, or gestures for enhanced accessibility.


[00048] In the description of the present invention, it is also to be noted that, unless otherwise explicitly specified or limited, the terms "fixed" "attached" "disposed," "mounted," and "connected" are to be construed broadly, and may for example be fixedly connected, detachably connected, or integrally connected, either mechanically or electrically. They may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.

[00049] Modifications to embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as "including", "comprising", "incorporating", "have", "is" used to describe and claim the present disclosure are intended to be construed in a non- exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.

[00050] Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the present disclosure, the drawings and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.

, Claims:WE CLAIM:
1. A control mechanisms for electronic devices with artificial intelligence capabilities 100 comprising of
data acquisition unit 102 to collect real-time data from embedded sensors;
data processing module 104 to analyze collected data using machine learning algorithms;
decision-making engine 106 to formulate control strategies based on analyzed data;
user interaction interface 108 to provide real-time feedback and capture user preferences;
connectivity module 110 to enable communication with other devices and cloud platforms;
adaptive learning algorithm 112 to refine control strategies based on historical and real-time data;
multi-sensor integration 114 to collect comprehensive data from various sensors for better decision-making;
edge computing capability 116 to process data locally for faster decision-making;
cloud connectivity and data synchronization 118 to sync data across devices and enable remote monitoring;
intelligent resource management module 120 to optimize energy consumption and performance;
self-diagnostics and maintenance alerts 122 to monitor device health and alert for maintenance;
interoperability framework 124 to ensure seamless communication with external systems and platforms;
privacy and security features 126 to encrypt data and secure device communications;
dynamic user feedback loop 128 to continuously collect and incorporate user input for refinement;
context-aware operation 130 to adjust device behavior based on situational data;
energy harvesting capabilities 132 to generate power from renewable sources;
multi-modal interaction interface 134 to enable control through voice, touch, or gestures.

2. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein data acquisition unit 102 is configured to collect real-time data from embedded sensors, including temperature, humidity, motion, and energy consumption, to monitor the device's operational environment and provide continuous input for analysis and control.

3. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein data processing module 104 is configured to analyze the collected data using machine learning algorithms, identifying patterns and trends for decision-making and device performance optimization.

4. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein decision-making engine 106 is configured to formulate control strategies autonomously based on insights provided by the data processing module 104, enabling real-time adjustments to the device's operational performance.

5. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein user interaction interface 108 is configured to provide real-time feedback to the user, capture manual adjustments, and integrate user preferences into the system's control algorithms for personalized operation.

6. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein connectivity module 110 is configured to enable communication with other smart devices, cloud platforms, and external systems, facilitating data sharing, synchronization, and collaborative operation within an interconnected ecosystem.

7. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein adaptive learning algorithm 112 is configured to refine the control strategies continuously by learning from historical data, user interactions, and real-time environmental changes, ensuring optimal device performance.

8. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein intelligent resource management module 120 is configured to optimize energy consumption and operational efficiency by adjusting the device's resource usage based on real-time data and predictive analysis.

9. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein self-diagnostics and maintenance alerts 122 are configured to monitor device health, detect potential issues, and alert the user for preventive maintenance to minimize downtime and improve reliability

10. The control mechanism for electronic devices with artificial intelligence capabilities 100 as claimed in claim 1, wherein method comprises of
data acquisition unit 102 collecting real-time data from embedded sensors to monitor the device's operational environment;

data processing module 104 analyzing the collected data using machine learning algorithms and forwarding insights to decision-making engine 106;

decision-making engine 106 formulating control strategies based on the analyzed data and adjusting the device's performance accordingly;

user interaction interface 108 providing feedback to the user and integrating manual adjustments into the system's control algorithms;

connectivity module 110 facilitating communication with other smart devices and platforms for data sharing and synchronization;

adaptive learning algorithm 112 refining control strategies based on historical data and real-time user interactions;

intelligent resource management module 120 optimizing energy consumption and performance based on real-time and predictive data;

self-diagnostics and maintenance alerts 122 monitoring device health and alerting the user for preventive maintenance;

interoperability framework 124 ensuring compatibility and seamless communication with external systems through connectivity module 110;

privacy and security features 126 encrypting data and securing communications within the device network;

dynamic user feedback loop 128 continuously collecting and incorporating user input to refine system performance;

context-aware operation 130 adjusting device behavior based on situational data like time of day or user location;

energy harvesting capabilities 132 generating power from renewable sources to reduce reliance on external power;

multi-modal interaction interface 134 enabling user control through voice, touch, or gestures for enhanced accessibility

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