Lianyou Technology Car IoT Platform: Architecture, Data Ingestion, Storage, and Application Overview
The article presents a comprehensive overview of Lianyou Technology's car IoT platform, detailing its four‑layer architecture, configurable data ingestion, hybrid cloud storage solutions, real‑time and offline data warehouses, and downstream data applications such as user operation, intelligent recommendation, and data security practices.
Lianyou Technology, a provider of end‑to‑end solutions for the automotive industry, offers a car IoT platform built on four layers: cloud services, vehicle connection service platform, application service platform, and terminal services, supporting multi‑brand, multi‑model, and multi‑protocol connectivity with high availability and security.
The platform’s data flow is divided into three stages—data ingestion, data storage, and data access. Raw data from vehicles and devices are collected via configurable ingestion modules, routed to a Kafka message queue, and then persisted to a real‑time warehouse (Kafka + Redis) and an offline warehouse (Hive + HDFS).
Data storage utilizes a hybrid approach: real‑time analytics are powered by Doris, multi‑dimensional analysis by Kyligence, flexible ad‑hoc queries by ClickHouse, and search capabilities by Elasticsearch. The offline warehouse feeds BI tools such as Tableau via Kyligence and supports batch processing with Sqoop and scheduling via Azkaban.
Downstream data applications include offline user operation (tagging, segmentation for marketing), real‑time intelligent recommendation (scene recognition, content matching, arbitration), and various APIs that expose unified data services to apps, H5 pages, and operational platforms.
Data security and compliance are addressed by obtaining user consent before collection, retaining raw location data for seven days, and retaining derived privacy‑enhanced data for up to 30 days, with systematic cleanup of expired data.
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