一种AEMS推训一体机

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The AEMS push-training all-in-one machine, which integrates a data acquisition gateway, memory, storage, CPU, and GPU modules, solves the problems of data acquisition and analysis separation, cloud training limitations, and lack of localized decision-making in existing technologies, and achieves efficient, secure, and flexible energy management and data processing.

CN224519254UActive Publication Date: 2026-07-17BEIJING CAPITAL AIRPORT ENERGY SAVING TECH SERVICE CO LTD

Patent Information

Authority / Receiving Office: CN · China
Patent Type: Utility models(China)
Current Assignee / Owner: BEIJING CAPITAL AIRPORT ENERGY SAVING TECH SERVICE CO LTD
Filing Date: 2025-06-25
Publication Date: 2026-07-17

AI Technical Summary

Technical Problem

Existing intelligent devices suffer from limitations in data acquisition and intelligent analysis, cloud-based training modes, and a lack of localized intelligent decision-making capabilities. Furthermore, traditional energy management systems lack natural language interaction capabilities, resulting in high data latency, slow response times, significant privacy risks, and inflexible and inefficient energy management strategies.

Method used

The AEMS push-training all-in-one machine integrates a data acquisition gateway module, a memory module, a storage module, a CPU module, and a GPU module to achieve integrated data acquisition and intelligent analysis at the edge. The CPU module performs overall control and management, while the GPU module performs parallel computing acceleration. Combined with the DeepSeek14B acceleration unit and the edge storage array, localized data processing and analysis are realized.

Benefits of technology

It improves data processing efficiency, optimizes energy consumption, enhances system reliability and stability, facilitates deployment and maintenance, reduces data transmission costs and privacy leakage risks, and enables real-time and flexible energy management.

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Abstract

本申请提供了一种AEMS推训一体机，该AEMS推训一体机包括箱体，所述箱体内设置有采集网关模块、内存模块、存储模块、CPU模块和GPU模块，所述采集网关模块，用于从多种外部数据源实时采集数据，并把采集到的数据发送给所述内存模块和所述存储模块；所述内存模块，用于暂时存储所述采集网关模块传输过来的数据；所述存储模块，用于长期存储数据；所述CPU模块，用于AEMS推训一体机的整体控制和管理；所述GPU模块，用于AEMS推训一体机的并行计算加速。在上述技术方案中，实现了边缘侧的数据采集与智能分析一体化，提高了训练效率，优化了能耗。

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Claims

1. An AEMS training and pushing integrated machine, characterized in that, The system includes a housing, which houses a data acquisition gateway module, a memory module, a storage module, a CPU module, and a GPU module. The data acquisition gateway module is connected to the memory module and the storage module respectively, and is used to acquire data from multiple external data sources in real time and send the acquired data to the memory module and the storage module. The memory module is used to temporarily store the data transmitted from the acquisition gateway module; The storage module is used for long-term data storage; The CPU module is used for the overall control and management of the AEMS push-training integrated machine; The GPU module is used for parallel computing acceleration of the AEMS push-training integrated machine; The enclosure contains a power module, which is used to supply power. The enclosure includes a first cavity and a second cavity, wherein, The power module and the data acquisition gateway module are disposed within the first cavity; The memory module, the storage module, the CPU module, and the GPU module are disposed within the second cavity.

2. The AEMS push-training integrated machine of claim 1, wherein, A heat dissipation structure is provided on the outer wall of the enclosure.

3. The AEMS push-training integrated machine of claim 2, wherein, The heat dissipation structure includes an array of heat dissipation holes and a heat dissipation fan, wherein... The cooling fan is detachably connected to the outer wall of the housing.

4. The AEMS push-training integrated machine according to claim 3, characterized in that, The memory module, the CPU module, and the GPU module are integrated into a single unit.

5. The AEMS push-training integrated machine of claim 4, wherein, The memory module, the CPU module, and the GPU module are integrated on the motherboard.

6. The AEMS training and pushing integrated machine of claim 5, wherein, The acquisition gateway module integrates a DeepSeek14B acceleration unit, which is fixedly connected to the inner wall of the enclosure. The DeepSeek14B acceleration unit is used for edge-side data acquisition and AI training / inference integration.

7. The AEMS training and pushing integrated machine of claim 6, wherein, The DeepSeek14B acceleration unit includes a heterogeneous computing module consisting of an FPGA and an NPU. This FPGA and NPU module are fixedly connected to the inner wall of the enclosure. The FPGA and NPU heterogeneous computing module is used for edge-side data acquisition and AI training / inference integration.

8. The AEMS training and pushing integrated machine of claim 7, wherein, The model of the heterogeneous computing module consisting of the FPGA and NPU is XCZU19EG.

9. The AEMS push-training integrated machine of claim 8, wherein, The storage module includes an edge storage array, which is fixedly connected to the inner sidewall of the enclosure. The edge storage array is used for real-time data storage.

10. The AEMS push-training integrated machine of claim 9, wherein, The edge storage array is a dual-channel NVMeSSD, and the dual-channel NVMeSSD is fixedly connected to the inner sidewall of the enclosure.