SMART DASHBOARD FOR IOT SYSTEMS USING AI AND MATHEMATICAL IMAGE PROCESSING

Abstract

The invention in the proposed system introduces a Smart Dashboard for Internet of Things (IoT) systems, designed to enhance data visualization and decision-making through the integration of Artificial Intelligence (AI) and mathematical image processing techniques. This dashboard offers real-time monitoring and analysis of IoT devices, utilizing AI-driven algorithms to process and interpret complex data patterns. By leveraging mathematical methods for image recognition and pattern detection, the system can automatically identify anomalies, trends, and actionable insights from IoT sensor data, improving system efficiency and reliability. The user-friendly interface provides comprehensive visualizations, enabling stakeholders to interact with data effortlessly and make informed decisions. This smart dashboard is adaptable across various IoT applications, including smart cities, industrial automation, and healthcare, fostering an intelligent, data-driven environment.

Specification

Description:Title:

Smart Dashboard for IoT Systems Using AI and Mathematical Image Processing

Field of the Invention


[0001]
The present invention relates to smart dashboards for Internet of Things (IoT) systems, focusing on improving data visualization, real-time monitoring, and decision-making. Specifically, the invention integrates Artificial Intelligence (AI) and mathematical methods for image processing and pattern detection, enhancing automation, control, and optimization across various IoT applications.
Background
[0002] With the increasing adoption of IoT in various industries, the amount of data generated by sensors and devices is growing exponentially. Traditional dashboards in IoT systems are limited to basic data visualization without offering advanced analytics or real-time intelligence.
[0003] AI-driven systems are crucial in interpreting complex IoT data, while mathematical image processing is necessary for pattern recognition and anomaly detection, especially in visual data streams like images and videos.
[0004] The need for smart dashboards arises due to the limitations of current systems, which fail to incorporate advanced AI techniques for predictive analytics and image recognition, making it difficult for operators to make data-driven decisions efficiently.
[0005] All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.
[0006] In some embodiments, the numbers expressing quantities of ingredients, properties such as concentration, reaction conditions, and so forth, used to describe and claim certain embodiments of the invention are to be understood as being modified in some instances by the term "about." Accordingly, in some embodiments, the numerical parameters set forth in the written description and attached claims are approximations that can vary depending upon the desired properties sought to be obtained by a particular embodiment. In some embodiments, the numerical parameters should be construed in light of the number of reported significant digits and by applying ordinary rounding techniques. Notwithstanding that the numerical ranges and parameters setting forth the broad scope of some embodiments of the invention are approximations, the numerical values set forth in the specific examples are reported as precisely as practicable. The numerical values presented in some embodiments of the invention may contain certain errors necessarily resulting from the standard deviation found in their respective testing measurements.
[0007] As used in the description herein and throughout the claims that follow, the meaning of "a," "an," and "the" includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise.
[0008] The recitation of ranges of values herein is merely intended to serve as a shorthand method of referring individually to each separate value falling within the range. Unless otherwise indicated herein, each individual value is incorporated into the specification as if it were individually recited herein. All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. "such as") provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non- claimed element essential to the practice of the invention.
Summary of the Invention
[0009] Smart Dashboard for IoT Systems: The invention integrates a smart dashboard for Internet of Things (IoT) systems to enable real-time monitoring, analysis, and control.
[0010] AI-Driven Analytics: The system uses Artificial Intelligence (AI) algorithms to analyze data from IoT sensors, providing predictive insights and detecting anomalies.
[0011] Mathematical Image Processing: The dashboard incorporates mathematical methods for image recognition and pattern detection, enhancing the system's ability to process and interpret visual data from IoT devices like cameras.
[0012] Real-Time Data Visualization: It provides a user-friendly interface displaying real-time metrics, alerts, and historical data trends, allowing users to monitor the IoT network efficiently.
[0013] Automation and Control: The system includes an automation module that sends feedback to IoT devices, enabling autonomous adjustments and automatic control based on AI analysis and detected patterns.
[0014] Application Areas: The smart dashboard is applicable in various fields, including smart cities, industrial automation, and healthcare, fostering improved decision-making and system efficiency.
Objects of the Invention
[0015] The primary object of the invention is to provide a smart dashboard that integrates AI algorithms and mathematical methods for advanced data analysis, anomaly detection, and real-time visualization in IoT environments.
[0016] Another object is to develop a user-friendly interface that allows users to easily monitor, analyze, and interpret IoT data, leading to better decision-making and automation of processes.
[0017] Further, the invention aims to improve the accuracy of image recognition and pattern detection in IoT systems through sophisticated mathematical techniques, enabling systems to detect trends, anomalies, and insights that traditional systems miss.
Advantages of the Invention
[0018] The smart dashboard enhances IoT system efficiency by leveraging AI-driven analysis to provide real-time, actionable insights.
[0019] The integration of mathematical image processing improves the system's ability to detect patterns and anomalies, ensuring proactive management of IoT devices.
[0020] The user interface simplifies complex data interpretation, making the system adaptable to various industries like smart cities, industrial automation, and healthcare.
Drawings

Figure 1

Brief Description of the Drawing

[0021] Figure 1 represents the system architecture for the Smart Dashboard for IoT Systems Using AI and Mathematical Image Processing. The figure illustrates the flow of data from various IoT devices, through the machine learning and mathematical image processing modules, and into the smart dashboard, which visualizes and processes the data for real-time monitoring, analysis, and decision-making.
Detailed Description of The Invention

[0022] In figure 1, showing the input parameter; which is to be processed by the system 100.
[0023]This stage involves the collection of raw data by IoT devices such as sensors and cameras. These devices continuously gather real-time information related to environmental conditions, motion, image/video, temperature, or other relevant parameters.
[0024] Once collected, the data is transmitted to a central processing unit (CPU) where further analysis takes place. This transmission is done over a communication network, ensuring that the raw data reaches the CPU securely and in real-time.
[0025] In the next step of Local Data Processing and Initial Analysis, initial processing occurs locally, including filtering, pre-processing, and compression of the collected data. This helps reduce noise and prepare the data for further in-depth analysis.
[0026] Machine Learning-Based Predictive Analysis (106) is a key component of the system where machine learning algorithms are applied to the pre-processed data to detect patterns, predict future events, or identify anomalies. The machine learning module continually improves its predictive capabilities by learning from the data.
[0027] Based on the output of the machine learning module, context-aware decisions are made. This means that the system takes into account environmental and situational factors when making decisions to ensure accuracy.
[0028] At the stage of Personalized Automation and Control, the system applies the decisions made by the AI model to automate control over the IoT devices. For example, adjusting a thermostat or activating security measures in response to detected anomalies.
[0029] Intelligent alerts are generated to notify users or administrators of significant events, anomalies, or potential risks. The system also provides recommendations for actions that could improve efficiency or mitigate risks.
[0030] The system optimizes energy consumption by analyzing data related to the power usage of connected IoT devices. It can turn devices on/off or adjust settings to reduce unnecessary energy usage.
[0031] At the stage of Actionable Insights and Reporting (116) , the system provides detailed insights into system performance and data trends. The insights are displayed in a user-friendly manner via reports, enabling better decision-making by administrators.
[0032] Finally, the system implements continuous monitoring of the IoT devices and processes. The data generated from the dashboard is used in a feedback loop to make real-time adjustments to IoT devices and settings, ensuring optimal performance.
[0033] The invention introduces a smart dashboard that collects data from IoT devices, processes it through AI-based algorithms, and applies mathematical image processing to detect patterns and anomalies. The processed data is displayed on a user-friendly interface, providing insights for operators to make informed decisions.
[0034] IoT devices such as sensors and cameras are connected to a central system. The data flows into machine learning modules that analyze trends and predict real-time anomalies. Simultaneously, mathematical methods are applied to images and video streams for pattern detection.
[0035] The smart dashboard is capable of real-time monitoring and can trigger automated responses based on the data, such as adjusting the performance of devices or sending alerts.
[0036]
It should be apparent to those skilled in the art that many more modifications besides those already described are possible without departing from the inventive concepts herein. The inventive subject matter, therefore, is not to be restricted except in the spirit of the appended claims. Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms "comprises" and "comprising" should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refer to at least one of something selected from the group consisting of A, B, C …. and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.


, Claims:
We Claim:

1. A smart dashboard system for IoT, incorporating AI-driven algorithms and mathematical image processing techniques for real-time monitoring and pattern detection.
2. The system claimed in claim 1, wherein the dashboard provides automated insights and allows user interaction for decision-making based on data from IoT devices.
3. The system as claimed in claim 1, wherein the dashboard integrates machine learning models for anomaly detection and image processing algorithms for trend analysis.
4. A method for optimizing IoT system efficiency using the smart dashboard, consisting of collecting IoT data, processing the data through AI algorithms, applying mathematical image processing, and visualizing insights.

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