CLOUD-BASED AI SYSTEM FOR REAL-TIME DATA ANALYSIS AND PREDICTIVE INSIGHTS

Abstract

The present invention provides a cloud-based AI system for real-time data analysis and predictive insights, integrating advanced machine learning algorithms with a scalable cloud infrastructure. The system comprises modules for data ingestion, adaptive learning, predictive modeling, and user-friendly visualization, enabling efficient processing of diverse data streams from IoT devices, databases, and APIs. It dynamically optimizes resource allocation to ensure scalability and cost-efficiency while maintaining low latency. The system supports applications across industries, including predictive maintenance, personalized healthcare, and financial forecasting, and incorporates robust security protocols for data integrity and compliance.

Specification

Description:The present invention pertains to the domain of cloud computing and artificial intelligence, specifically focusing on a system for real-time data analysis and predictive insights. It leverages advanced machine learning algorithms, scalable cloud infrastructure, and adaptive learning techniques to process and analyze large volumes of data from diverse sources, providing actionable insights and optimizing decision-making across various industries, including healthcare, finance, manufacturing, and logistics.
BACKGROUND OF THE INVENTION
The following description of related art is intended to provide background information pertaining to the field of the disclosure. This section may include certain aspects of the art that may be related to various features of the present disclosure. However, it should be appreciated that this section be used only to enhance the understanding of the reader with respect to the present disclosure, and not as admissions of prior art.

In recent years, the rapid proliferation of data fr , Claims:1. A cloud-based AI system for real-time data analysis and predictive insights, comprising:
o a data ingestion module configured to acquire and preprocess real-time data from multiple sources,
o an AI engine hosted on a distributed cloud infrastructure for executing machine learning models,
o a prediction module configured to generate actionable insights and trend analysis, and
o a user interface for visualizing results in real-time.

2. The system of claim 1, wherein the AI engine includes a self-learning module that dynamically updates the machine learning models based on new incoming data.
3. The system of claim 1, further comprising a resource optimization module that allocates computational resources based on data load and processing requirements.
4. The system of claim 2, wherein the self-learning module utilizes reinforcement learning techniques to enhance prediction accuracy.
5. The system of claim 1, wherein the data ingestion module supports integration with IoT devices, third-party APIs, and cloud

Documents