Description:FIELD OF THE INVENTION
This invention relates to IoT-Powered Fitness Tracking with Personalized Guidance
BACKGROUND OF THE INVENTION
Fitness enthusiasts require a sophisticated system connecting with their home or gym equipment to track their progress, report results, and provide real-time feedback. Most current systems rely on user input or wearables but don't offer full machine integration for detailed analysis and workout modification.
US 11951357 B1 Platform for visual tracking of user fitness, published: Apr 9, 2024, Granted: Apr 9, 2024.
US 11351421 B2 Fitness equipment cruise control with power reserve, published: Jun 7, 2022, Granted: Jun 7, 2022.
The current method relies on camera-based identification, which can lead to incorrect input due to poor lighting, obstacles, or limited camera angles.
The existing system is based on "cruise control" virtual power reporting, which might not be a good indicator of the user's actual effort and could lead to misleading feedback about their workout results.
In contrast to current models that offer limited integration and generic feedback based on time or heart rate, the proposed model guarantees thorough integration with gym equipment utilizing Bluetooth and sensors, providing accurate real-time information on form, repetitions, weight, and fastness. Instead of requiring users to manually input data required by applications and separate devices, it automates the process using equipment sensors and wearables. By leveraging AI to provide personalized feedback and exercise suggestions, the proposed approach stands out from current systems that provide generic guidance and are sometimes ecosystem-specific, all while guaranteeing interoperability with a wide range of devices and wearables. In contrast to pricey systems or subscription-based services, it offers a cost-effective Internet of Things solution with a fully automated, real-time personalized experience.
In contrast to current models that offer limited integration and generic feedback based on time or heart rate, the proposed model guarantees thorough integration with gym equipment utilizing Bluetooth and sensors, providing accurate real-time information on form, repetitions, weight, and fastness. Instead of requiring users to manually input data required by applications and separate devices, it automates the process using equipment sensors and wearables. By leveraging AI to provide personalized feedback and exercise suggestions, the proposed approach stands out from current systems that provide generic guidance and are sometimes ecosystem-specific, all while guaranteeing interoperability with a wide range of devices and wearables. In contrast to pricey systems or subscription-based services, it offers a cost-effective Internet of Things solution with a fully automated, real-time personalized experience.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
The proposed system is illustrated in Figure 1. By connecting to fitness equipment through Bluetooth or sensors, the device records exercise data such as speed, number of repetitions, and weight lifted. Users can manually input data for exercises that do not involve machinery through an app. In the proposed method, smartwatches and other wearables track vital signs like heart rate, calorie expenditure, and motion, while attached sensors like accelerometers and force sensors record exercise data in real-time. To help users improve their workouts, artificial intelligence algorithms examine the collected data and assess the user's performance. The algorithms then provide personalized, real-time feedback on form, repetitions, and intensity. With the data stored in the cloud, exercise recommendations may be continuously analyzed and improved.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: BLOCK DIAGRAM OF PROPOSED SYSTEM
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms “a",” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", “third”, and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The proposed system is illustrated in Figure 1. By connecting to fitness equipment through Bluetooth or sensors, the device records exercise data such as speed, number of repetitions, and weight lifted. Users can manually input data for exercises that do not involve machinery through an app. In the proposed method, smartwatches and other wearables track vital signs like heart rate, calorie expenditure, and motion, while attached sensors like accelerometers and force sensors record exercise data in real-time. To help users improve their workouts, artificial intelligence algorithms examine the collected data and assess the user's performance. The algorithms then provide personalized, real-time feedback on form, repetitions, and intensity. With the data stored in the cloud, exercise recommendations may be continuously analyzed and improved.
The accompanying app allows users to see their workout data, get fitness advice, and personalize their routines. Personalized fitness plans, goal-oriented tracking, and group activities are all part of its functionality. Gym equipment with built-in speakers or screens gives users immediate feedback in the form of suggestions to improve form, adjust intensity, or maximize speed. A detailed report outlining the effectiveness of the workout as a whole, down to specific metrics like heart rate, weight, sets, and repetitions, is available to users after each session. To help users stay motivated and make the most of their fitness journey, the system provides personalized workout recommendations.
An IoT-Powered Fitness Tracking with Personalized Guidance comprising a weight sensor, a force sensor, a microcontroller, a Bluetooth and Wi-Fi hub, a Router, a display unit, a mobile application, a cloud storage, a wearable device, a power supply, an AI algorithm, wherein an algorithmic approach to real-time feedback that analyzes data from the weight sensor and force sensor on fitness equipment and wearable device, providing users with instantaneous feedback on their form, number of repetitions, and workout pace.
In another embodiment to help users improve their workouts, the microcontroller examines the collected data and assess the user's performance using artificial intelligence algorithms.
In another embodiment the artificial intelligence algorithms are used to make real-time adjustments to exercise recommendations based on user performance and fatigue levels and this helps to minimize injury risk and ensures that training sessions are intense enough.
In another embodiment the Bluetooth and Wi-Fi hub is used to wireless connectivity with the mobile application and wearable device.
In another embodiment the mobile app allows users to see their workout data, get fitness advice, and personalize their routines, that is connected with the system through the Bluetooth.
In another embodiment the router is used to connect the system to the cloud storage for use of historical data.
In another embodiment the system is rechargeable so the battery is used to supply the power for the system.
As opposed to competing wearables or camera-based systems, this gadget integrates smoothly with existing gym apparatus, allowing for the automated tracking of sets, weight, speed, repetitions, and repetitions without the need for manual intervention. Users can perform better and avoid injuries with the help of real-time, personalized feedback on their technique, speed, and effort. The system learns the user's habits and development over time through AI analysis, then provides personalized suggestions to help them lose weight or improve their body shape. In comparison to premium gym systems, it offers advanced capabilities at a lower cost and is compatible with a variety of gym equipment. It is an extensive training solution. Wearable devices can also be connected to it. 
Best Method of working
The core functionality of the system revolves around the seamless interaction between multiple components, each playing a specific role in ensuring the accurate collection, analysis, and feedback of workout data. The system is composed of several interconnected devices, including weight sensors, force sensors, a microcontroller, a Bluetooth and Wi-Fi hub, a router, a display unit, a mobile application, cloud storage, a wearable device, and an AI algorithm. Together, these components enable users to receive personalized workout feedback and performance insights in real-time.
1. Data Collection and Sensor Integration: The weight sensor and force sensor, embedded in fitness equipment, continuously monitor the load applied during exercises. These sensors capture data on the user’s exertion, including the weight lifted, the force exerted, and the number of repetitions performed. The wearable device also collects additional user data, such as movement patterns and heart rate, further enriching the system's analysis. These sensors communicate the data in real-time to the microcontroller.
2. Microcontroller and AI Algorithm: The microcontroller acts as the central hub for processing the incoming data from the weight sensor, force sensor, and wearable device. It then feeds this information into an AI algorithm that analyzes the performance of the user in real-time. The AI algorithm uses advanced machine learning models to assess key metrics, such as workout speed, form, and fatigue levels. This analysis enables the system to provide immediate feedback on the user's performance, making real-time adjustments to exercise recommendations.
The AI algorithms continuously evaluate the user’s progress and adapt the training program based on performance trends. For example, if the system detects that the user is showing signs of fatigue or improper form, it may recommend a decrease in intensity or adjustments in posture to prevent injury. This feature ensures that the workouts are tailored to the user's current state, maintaining the intensity necessary for progress while mitigating the risk of overtraining or injury.
3. Real-Time Feedback and User Interaction: Once the data is processed, the system provides immediate feedback to the user. The feedback is delivered through multiple interfaces: on a display unit, via the mobile application, or through the wearable device. The user is informed about their performance metrics, including the number of repetitions, the weight used, and their pacing. The system can offer suggestions for improving form and technique, ensuring that the user performs exercises correctly, reducing the risk of strain or injury.
4. Wireless Connectivity: To ensure seamless data transfer, the Bluetooth and Wi-Fi hub enables wireless connectivity between the system components, such as the wearable device, mobile application, and fitness equipment. The Bluetooth connectivity ensures that real-time data is efficiently transferred from the sensors to the microcontroller, while the Wi-Fi hub enables the system to sync with the mobile app and cloud storage. This allows users to access their data remotely, review their progress, and get personalized fitness advice at any time.
5. Cloud Storage and Historical Data Analysis: The system uses a router to connect to cloud storage, which stores historical workout data for each user. This cloud-based storage allows users to review their workout history, track long-term progress, and receive insights into their development over time. The AI algorithm also analyzes historical data to refine future workout recommendations, ensuring that the training remains progressive and effective.
6. Mobile Application and Personalization: The mobile application plays a critical role in connecting the user to the system, providing a user-friendly interface for reviewing workout data and accessing personalized guidance. Through Bluetooth connectivity, the mobile app syncs with the sensors and wearable device to display real-time metrics. Users can customize their workout routines within the app, setting goals for weight loss, strength gain, or body shape improvement. Additionally, the app provides motivational reminders, workout suggestions, and adjustments based on real-time performance, ensuring that users stay on track with their fitness journey.
7. Power Supply and Rechargeability: The system is designed to be energy-efficient, with a rechargeable battery providing power to the components. This battery ensures that users can rely on the system for extended periods, without needing to constantly recharge. The system can be recharged via a standard power supply, making it convenient for long-term use.
8. Advanced Features and Cost Efficiency: Unlike traditional fitness trackers or camera-based systems, this IoT-powered system integrates seamlessly with existing gym equipment, offering automated tracking without requiring manual input. This integration helps automate the tracking of sets, weights, speed, and repetitions, ensuring that users have a more efficient and accurate training session. The system’s real-time feedback ensures users can perform exercises with optimal form, preventing injuries and improving overall performance.
Moreover, the system is offered at a lower cost than premium gym setups, while providing more advanced capabilities. It is compatible with various gym equipment, allowing users to personalize their training according to their needs. This versatility makes it an ideal solution for users who wish to track their fitness performance in any gym setting, while also benefiting from personalized guidance.
, Claims:1. An IoT-Powered Fitness Tracking with Personalized Guidance comprising a weight sensor, a force sensor, a microcontroller, a Bluetooth and Wi-Fi hub, a Router, a display unit, a mobile application, a cloud storage, a wearable device, a power supply, an AI algorithm, wherein an algorithmic approach to real-time feedback that analyzes data from the weight sensor and force sensor on fitness equipment and wearable device, providing users with instantaneous feedback on their form, number of repetitions, and workout pace.
2. The system as claimed in claim 1, wherein to help users improve their workouts, the microcontroller examines the collected data and assess the user's performance using artificial intelligence algorithms.
3. The system as claimed in claim 1, wherein the artificial intelligence algorithms is used to make real-time adjustments to exercise recommendations based on user performance and fatigue levels and this helps to minimize injury risk and ensures that training sessions are intense enough.
4. The system as claimed in claim 1, wherein the Bluetooth and Wi-Fi hub are used to wireless connectivity with the mobile application and wearable device.
5. The system as claimed in claim 1, wherein the mobile app allows users to see their workout data, get fitness advice, and personalize their routines, that is connected with the system through the Bluetooth.
6. The system as claimed in claim 1, wherein the router is used to connect the system to the cloud storage for use of historical data.
7. The system as claimed in claim 1, wherein the system is rechargeable so the battery is used to supply the power for the system.