A central agent SDK interface with LLM backend for aggregating inputs from different home systems

Abstract

A central agent SDK interface with LLM backend for aggregating inputs from different home systems (100), comprising: (a) a software development kit (SDK) configured to interface with multiple home systems on different platforms without requiring direct hardware integration; b) a Large Language Model (LLM) backend that is communicatively connected to the SDK and configured to process and interpret diverse, unstructured or natural language inputs; c) a device and input aggregation module designed to identify and collect input data from various unconnected home systems via APIs, sensors, protocols or user input; (d) a data normalisation and contextualisation module configured to convert heterogeneous input data into a standardised format and to attach contextual metadata; (e) a Natural Language Understanding (NLU) module integrated into the LLM backend, configured to translate user requests and device signals into structured, actionable intents; f) an inference and reasoning engine configured to analyze normalized data, recognize behavioral patterns, and generate system-level decisions or recommendations; g) an Action Orchestration & Response Module configured to execute intelligent actions by communicating with home systems via software interfaces; h) a data protection and authorization management module to enforce policies for user consent, access control, and secure data processing; and i) an SDK and API gateway for developers configured to enable the integration, customisation and deployment of new device support or logic into the system by third parties.

Description

The present invention relates to systems for integrating and managing data from different non-interconnected home systems. In particular, it provides a central agent interface via an SDK supported by a large language model (LLM). This allows seamless aggregation, interpretation, and coordination of inputs across different home devices and platforms.Most modern households contain a large number of intelligent devices and systems such as thermostats, lighting, safety cameras and household appliances. However, these devices are often developed by various manufacturers and operate on isolated platforms, making their communication and efficient interworking difficult.Conventional solutions for home automation require integration via centralized hubs or proprietary ecosystems. These solutions often lack flexibility, require complex configurations, or do not support a wide range of third party systems, leading to fragmentation and inefficiencies.Moreover, the lack of a common interface for merging data from non-connected systems results in a limited understanding of the overall home environment. This hinders the ability to automate responses or make smart recommendations based on combined system data.With the advent of large language models (LLMs), it has become possible to process and interpret multiple, unstructured, and asynchronous inputs in a human-like and contextual manner. However, their potential has not yet been fully exhausted for decentralized integration of home systems.The present invention solves these challenges by introducing a central agent interface that is connected to an LLM backend via an SDK. This allows for consistent input aggregation, contextual interpretation, and cross-system coordination without requiring direct hardware interconnectivity.An object of the present disclosure is to enable seamless integration of non-connected home systems without hardware dependencies.Another object of the present disclosure is to utilize LLMs for intelligent contextual interpretation of various inputs.Another object of the present disclosure is to standardize heterogeneous data into a uniform, usable format.Another object of the present disclosure is to support natural language commands for intuitive user interaction.Another object of the present disclosure is to automate decision making through real-time inference and inferences.Another object of the present disclosure is to perform coordinated actions across multiple platforms and devices.Another object of the present disclosure is to provide data protection and user control through robust entitlement management.Another object of the present disclosure is extendibility via SDKs and APIs for future device and function integration.Other objects and advantages of the present disclosure will become apparent from the following description, which is not intended to limit the scope of the present disclosure.The present invention relates to a central agent interface having an SDK supported by a large language model (LLM) for unifying inputs from various non-interconnected home systems. It obviates hardware integration and instead focuses on intelligence and interoperability at the software level.Another embodiment of the present invention is the Device & Input Aggregation Module, which collects data from different household appliances, sensors and platforms without having to be in the same network. This allows the system to recognize and interact with fragmented sources of information.Another embodiment of the present invention is the Data Normalization & Contextualization Module, which normalizes incoming data formats and adds contextual metadata. This ensures that the system can reasonably interpret inputs over time, location and device types.Another embodiment of the present invention is the Natural Language Understanding (NLU) module that uses LLM capabilities to interpret human input and unstructured data. It naturally translates language queries or commands into implementable tasks for the system.Another embodiment of the present invention is the Interference & Reassoning module, which derives findings from the analysis of aggregated and normalized data. It can recognize trends, predict needs, and recommend or initiate responses across disconnected systems.Another embodiment of the present invention, the Action Orchestration & Response Module, performs system-wide responses through interfaces to device APIs or cloud services. It ensures that the actions are context related and coordinated regardless of the origin of the device.Another embodiment of the present invention is the Privacy & Mission Management Module that manages user approval, data encryption, and access control. It protects personal information and at the same time ensures secure coordination across the device.Another embodiment of the present invention is the developer's SDK & API gateway, which provides extension capabilities and allows developers to incorporate new devices or logic. This makes the system future safe and promotes an customizable open ecosystem for home automation.The present invention relates to a central agent interface system that merges inputs from different non-interconnected home systems (100) using an SDK and a large language model (LLM). It comprises seven key modules: aggregation of devices and inputs, normalization and context normalization of data, NLU (Natural Language Understanding) module, inference and reasoning module, Action Orchestration & Response, Privacy & Mission Management, and Developer SDK & API Gateway. These modules cooperate to collect, standardize, interpret, and react to data from various devices without requiring direct hardware integration. The LLM naturally allows for voice interactions and intelligent decision making across all platforms. This architecture provides a flexible, secure and extensible solution for modern smart home automation.The invention is explained again below with reference to the figure. The following shows: FIG. 1 is an illustration of a central agent SDK interface with LLM backend for aggregating inputs from different home systems (100).FIG. 1 illustrates a central agent SDK interface with LLM backend for aggregating inputs from different home systems ( 100). The system consists of seven core modules: device aggregation and input module that identifies available devices and systems throughout the home and collects data from sensors, APIs, protocols, and user inputs without requiring direct hardware connectivity; data normalization and contextualization module that converts heterogeneous input formats into a unified data structure and enriches them with contextual metadata such as time, location, or usage patterns; Natural Language Understanding (NLU) module that is based on a large language model that processes unstructured user commands, queries, and device signals and interprets them in implementable intents; Interference & Responding module that analyzes combined data streams to derive insights, recognize patterns, and make smart decisions or recommendations for otherwise isolated systems; Action Orchestration & Response Module that initiates appropriate actions such as notifications, commands, or routines via interfaces to third party APIs or systems and ensures coherent execution across platforms; Privacy & Mission Management Module that ensures user control, data security, and access control through the implementation of entitlement rules, encryption, and anonymization protocols; and Developer SDK & API Gateway, which offers external developers tools and interfaces for the integration of new devices, the creation of user-defined logic and the expansion of the system functions. Together, these modules form a coherent architecture that enables contextual automation and intelligent control of fragmented home technologies without requiring users to migrate to a single provider or platform.

Claims

A central agent SDK interface with LLM backend for aggregating inputs from different home systems (100), comprising: a) a software development kit (SDK) configured to interface with multiple home systems on different platforms without requiring direct hardware integration; b) a large language model (LLM) backend communicatively coupled to the SDK and configured to process and interpret various, unstructured, or natural language inputs; c) a device aggregation module and inputs configured to identify and collect input data from different non-coupled home systems via APIs, sensors, protocols, or user inputs; d) a data normalization and context normalization module configured to convert heterogeneous input data to a standardized format and to add context-related metadata; e) a natural language understanding (NLU) module integrated into the LLM backend configured to translate user requests and device signals into structured, implementable intents; f) an inference & reasoning engine configured to analyze normalized data, recognize behavioral patterns, and generate system-level decisions or recommendations; g) an action orchestration & response module configured to perform intelligent actions by communicating with home systems via software interfaces; h) a privacy and entitlement management module for enforcing policies for user approval, access control, and secure data processing; and i) a developer SDK and API gateway configured to enable third party integration, adaptation, and provision of new device support or logic into the system.The system (100) of claim 1, wherein the device and input aggregation module further supports real-time data collection of cloud-based services, mobile applications, and IoT devices.The system (100) of claim 1, wherein the data normalization and contextualization module applies machine learning techniques to dynamically derive missing contextual information from input data.The system (100) of claim 1, wherein the natural language understanding (NLU) module is further configured to process multimodal input including speech, text and gesture based commands.The system (100) of claim 1, wherein the inference and reasoning engine includes predictive analyses to predict user behavior or system needs based on historical data and contextual analyses.The system (100) of claim 1, wherein the action orchestration & response module enables customizable execution of instructions that allow prioritization of actions based on user preferences or environmental conditions.The system (100) of claim 1, wherein the privacy and entitlement management module further comprises functions for end-to-end encryption and real-time verification of data access and system interactions.The system (100) of claim 1, wherein the developer SDK & API gateway provides integrated support for integrating third party devices and services using standardized protocols such as RESTful APIs or MQTT.

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