Description:FIELD OF THE INVENTION
This invention relates to Real-time analytics and adaptive content delivery in an intelligent IoT-driven interactive learning system.
BACKGROUND OF THE INVENTION
Real-time analytics and adaptive material distribution in an Internet of Things (IoT)-driven interactive learning system seem to personalize education through the usage of devices to monitor student performance. Every student in our previous educational system had their own philosophy, and teaching the same subject to different students can be difficult. Students also struggle to receive the same instruction for all of these reasons, which leads to the educational system's failure. Since these youngsters are not getting enough information, we need a monitoring system that can determine the children's ideologies and automatically adapt the content to fit their preferences. Disengagement results from traditional teaching approaches' inability to fulfill each student's unique learning demands. inadequately timely feedback.
By analyzing sensor data and providing tailored information, this technology enhances learning opportunities and helps educators better meet the requirements of their pupils.
CN112836036AInteractive training method, device, terminal and storage medium for intelligent agent
Because of the lack of real-time feedback and the absolutely necessary teacher interventions, current personalized learning solutions frequently fall short. This forces a reliance on static content delivery, which leaves students feeling overloaded or distracted and prevents real-time interaction. Many systems only use fragmented data, which makes it impossible to evaluate student outcomes. For this reason, we need IoT technologies that can collect and analyse data from various platforms and comprehend the unique demands of every single student.
The previous solutions had certain advantages, but the proposed solution offers several improvements. Firstly, compared to the previous one, the proposed solution is more effective. It stands out by incorporating novel technologies or approaches that differentiate it from earlier solutions. Secondly, while the previous solution was more scalable, the new one specifically targets a more focused audience. Regarding cost-effectiveness, the previous solutions reduced labor costs and expenses, but the proposed solution is implemented in a way that requires less deployment and offers quicker setup times. Additionally, the proposed solution enhances user outcomes and improves accessibility, an area where the previous solutions were lacking. Lastly, the new solution is more flexible and sustainable compared to existing systems. Its design and architectural framework differ from previous iterations, contributing to better performance and functionality.
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.
The present invention relates to a real-time analytics and adaptive content delivery system in an intelligent IoT-driven interactive learning platform. The system comprises a plurality of sensors, a wearable device, a microcontroller, cloud storage, and an adaptive learning system. The wearable technology and IoT sensors are used to track student learning progress, including eye movements and the time spent by each student. These sensors enable real-time analysis of student progress and evaluations, allowing the platform to dynamically modify content based on each student's learning needs.
In addition, the IoT system is used to control other aspects of the campus, such as safety monitoring, classroom environment adjustments, and access control, thereby enhancing both the learning experience and security. The microcontroller processes raw data collected from the sensors, enabling real-time decision-making and content adaptation. The adaptive learning system creates individual learner profiles using sensor data and adjusts the content to be more challenging or remedial based on the learner’s progress, ensuring consistent educational development for all students.
The platform allows teachers to modify content and implement customized interventions, generating detailed reports on student performance. Cloud storage is utilized to store historical student data for long-term analysis and adaptive content improvements. The cloud-connected adaptive learning system processes richer data insights, monitors long-term learning trends, and suggests content adjustments based on both real-time and historical student data. To ensure the security and privacy of student data, the system employs strong data encryption and complies with student privacy laws such as FERPA and GDPR.
Finally, the system includes a display that functions as a user interface to show the final results and facilitate interaction between the system, students, and educators. This invention overcomes the limitations of current solutions by providing a real-time, adaptive learning environment that utilizes IoT sensors, edge computing, and cloud analytics to personalize educational content based on immediate student engagement and input.
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 block diagram for proposed innovation is Real-time analytics and adaptive content delivery in an intelligent IoT-driven interactive learning system illustrated in Fig. 1. The system consists of a sensor, wearable devices, microcontroller boards, cloud storage, LMS, HVAC sensors.
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 INNOVATION
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 block diagram for proposed innovation is Real-time analytics and adaptive content delivery in an intelligent IoT-driven interactive learning system illustrated in Fig. 1. The system consists of a sensors, wearable devices, microcontroller boards, cloud storage, LMS, HVAC sensors.
It overcomes the shortcomings of current solutions by utilizing IoT devices to develop an entirely responsible and adaptable educational platform.
Wearable technology and Internet of Things sensors are used in the solution to track student learning progress over time, including eye movements and the amount of time spent with each student. These sensors allow the system to analyze student progress and evaluations in real time, allowing it to quickly modify the content according to the students' learning. As a result, the system can offer additional content to give a clear explanation if a student is struggling with a certain subject. The platform creates a profile for every learner using sensors, like cameras or other gadgets. It alters the information according to this profile to make it more difficult or re-medial for kids who need extra assistance, ensuring that every student makes the same amount of progress. Compared to a typical method, this produces good progress and collects student data in the right way. By making modifications and putting customized interventions into place, teachers can subsequently obtain a thorough report on student performance. The IoT system can be used to control other aspects of campuses and schools, like safety monitoring and classroom environment. For example, it can detect unauthorized access to restricted areas or automatically adjust the lighting and temperature based on occupancy to create a safe and comfortable learning environment. This system would merge IoT-enabled classrooms with connected sensors and edge computing devices to process the data locally for quick adjustments. Surrounded by cloud infrastructure, the central analytics
The engine would handle richer data insights, monitor long-term learning trends, and suggest adaptive content. In order to protect student data and reduce the risk of unwanted access, this system would employ strong data encryption and guarantee compliance with laws like FERPA and GDPR. As a result, our IoT-driven adaptive platform offers a more secure, effective, and customized learning environment that caters to the individual needs of every student, improving engagement and academic results. make it little, shorter.
A Real-time analytics and adaptive content delivery in an intelligent IoT-driven interactive learning system comprising a number of sensors, a wearable device, a microcontroller, a cloud storage, an adaptive learning system, a display, wherein Wearable technology and Internet of Things sensors are used in the solution to track student learning progress over time, including eye movements and the amount of time spent with each student; Wherein these sensors allow the system to analyze student progress and evaluations in real time, allowing it to quickly modify the content according to the students' learning; Wherein the IoT system used to control other aspects of campuses and schools.
In another embodiment the microcontroller used to process the raw data that are collected from the sensors; Wherein the platform creates a profile for every learner using sensors and alters the information according to this profile to make it more difficult ore-medial for kids who need extra assistance, ensuring that every student makes the same amount of progress; Wherein By making modifications and putting customized interventions into place, teachers can subsequently obtain a thorough report on student performance.
In another embodiment the cloud storage used to store the historical data for further work. In another embodiment the adaptable learning system, that is connected with clod server, handle richer data insights, monitor long-term learning trends, and suggest adaptive content; Wherein In order to protect student data and reduce the risk of unwanted access, this system would employ strong data encryption and guarantee compliance with laws like FERPA and GDPR. In another embodiment the display work as the user interface that used to shown the final result.
In contrast to current solutions that lack continuous and automated content adjudication, this concept presents a real-time and adaptable learning platform that uses IOT sensors, edge computing, and cloud analytics to personalize educational content based on immediate student involvement and input. 
, Claims:1. A real-time analytics and adaptive content delivery system in an intelligent IoT-driven interactive learning platform, comprising a plurality of sensors, a wearable device, a microcontroller, cloud storage, and an adaptive learning system, where the wearable technology and IoT sensors track student learning progress, including eye movements and time spent by each student.
2. The system as claimed in claim 1, wherein the sensors enable real-time analysis of student progress and evaluations, allowing the platform to dynamically modify content based on each student's learning needs.
3. The system as claimed in claim 1, wherein the IoT system controls additional campus functions, such as safety monitoring, classroom environment adjustments, and access control, for enhanced learning and security.
4. The system as claimed in claim 1, wherein the microcontroller processes raw data collected from the sensors, enabling real-time decision-making and content adaptation.
5. The system as claimed in claim 1, wherein the adaptive learning system creates individual learner profiles using sensor data, adjusting content to be more challenging or remedial based on the learner’s progress, ensuring consistent educational development.
6. The system as claimed in claim 1, wherein the platform allows teachers to modify content and implement customized interventions, generating detailed reports on student performance.
7. The system as claimed in claim 1, wherein the cloud storage stores historical student data for long-term analysis and adaptive content improvements.
8. The system as claimed in claim 1, wherein the cloud-connected adaptive learning system processes richer data insights, monitors long-term learning trends, and suggests content adjustments based on real-time and historical student data.
9. The system as claimed in claim 1, wherein the system employs data encryption and ensures compliance with student privacy laws such as FERPA and GDPR to protect student data.
10. The system as claimed in claim 1, wherein the display functions as a user interface to show the final results and provide interaction with the system for both students and educators.