Unplanned Downtime Reduction
Proprietary AI time-series anomaly detection shifts from reactive repair to predictive early warning
DTU / Sensor Compatibility
MQTT, Modbus-RTU/TCP standard protocols — reuse existing equipment
Rapid Onboarding
No production line modification needed — standard protocol devices connected quickly
Industry Scenarios
Manufacturing | Energy | Aquaculture | Elevator | Warehouse
Data sources: Average hourly loss from unplanned downtime in SMEs: ¥5,000 (China Association of Plant Engineering, 2025); Traditional threshold alarm false-positive rate >40% (IEEE Trans. on Industrial Informatics, 2024); Factory energy leakage accounts for 8-15% of total consumption (National Energy Conservation Center).
Why do equipment failures always seem to happen out of nowhere?
It's not that your O&M team isn't working hard — the tools just haven't kept up. From reactive firefighting to proactive early warning, the missing piece is an AI monitoring system that learns and closes the loop.
Traditional Approach
固定阈值告警
越过门限才报警，缓慢劣化看不见；一次故障刷屏几十条无效告警，真正风险被淹没。
Platform Solution
AI 时序异常识别
学习每台设备自身运行基线，识别缓慢漂移与隐性异常。误报率降低 80%，告警分级推送给对的人。
Traditional Approach
电话/群消息通知
告警发到群里，谁处理、处理没处理全靠追问。夜间告警被淹没，第二天才发现。
Platform Solution
企微/短信分级推送 + 工单自动流转
按紧急程度分级分人推送，超时未确认自动升级。告警 → 工单 → 处理 → 归档全程留痕。
Traditional Approach
改造需停工、成本高
新建监测系统往往需要重新布线、更换设备、产线停工配合，项目周期长、影响生产。
Platform Solution
复用现有传感器，插电即上线
兼容市面 95% DTU/传感器，MQTT/Modbus 标准协议接入。不改造产线，30 分钟完成数据对接。
Full-Stack AIoT capabilities — the invisible guardian of your equipment
Five steps to close the loop: Connect, Store, Detect, Visualize, Resolve. Peace of mind for every operation.
AI智能告警引擎
传统监测只有固定阈值报警，容易产生大量误报、告警风暴。平台内置AI时序分析模型，学习设备历史运行规律…
Click for details多协议设备接入
支持MQTT、Modbus-RTU/TCP等主流工业物联网协议，兼容市面成熟DTU、传感器，无需自研…
Click for details时序数据存储与回放
基于时序数据库，海量设备传感器数据存储，长时间历史曲线查询，回溯设备故障全过程，用于故障复盘。…
Click for details可视化数据看板
实时总览所有设备在线状态、实时参数、告警统计，自定义看板，支持PC网页查看。…
Click for details移动端工单闭环
告警事件一键生成维保工单；维保人员微信小程序接收告警、接单、现场签到、拍照存档，工单全流程闭环管理。…
Click for detailsYour factory is facing these three hidden losses
Data sourced from authoritative industry reports and academic research. ZHIYUAN AIoT believes data is the greatest productivity, and safety is the greatest efficiency.
¥5,000/小时
中小工厂因设备突发停机，平均每小时损失
中国设备管理协会 2025 调研报告40%
传统阈值告警误报率超 40%，导致真正风险被淹没
IEEE Trans. on Industrial Informatics, 20248-15%
能耗跑冒滴漏占工厂总能耗，人工难以发现
国家节能中心 工业能效报告ZHIYUAN AIoT Factory Monitoring — Early Adopter Recruitment
Let's turn "no reference cases" into "let's build the first case together." Limited free pilot deployment slots — test the value of ZHIYUAN AIoT's early warning AI in your real production environment.
- Free or 50% off monitoring point fees during pilot
- Permanent logo and brand name display on our website
- Priority customization of alert rules and dashboards
- Free "Factory Energy Consumption & Equipment Health Analysis Report"
Apply for Pilot
Limited to the first 3 companies
A Unified AIoT Monitoring Platform Across Industries & Equipment
Five core scenarios — from equipment early warning to energy management, from farming environments to specialized equipment — all covered by one platform.
30-Minute Quick Onboarding, 24/7 Online Guardian
Not a one-off project — a long-term partnership. Data-driven from day one, so every operation runs with peace of mind.
30-Minute Quick Onboarding
Standard protocol devices use our point table template. Data reporting and integration completed within 30 minutes. Complex protocols evaluated separately — no over-promising.
7×24 Dedicated Support
Business hours tech support hotline + always-on alert monitoring channel. Real-time emergency response — no issue left overnight.
Data Security Assurance
Encrypted transmission + tiered time-series storage. Data retention based on subscription plan. Key data can be exported periodically by customers.
Start Your Free Trial — First 3 Companies Deploy for Free
Submit your site info. We will provide monitoring point recommendations, access methods, and pricing estimates. Pilot first, then scale — alerts are just the beginning; closed-loop resolution is where value lies.
They Are Already Using ZHIYUAN AIoT
电梯维保公司
电梯智能监测告警与维保工单数字化
电梯维保公司｜电梯智能监测告警项目
试点客户招募中
制造工厂
空压机与水泵机电设备状态监控
制造工厂｜空压机/水泵机电设备状态监控
试点客户招募中
养殖场
养殖环境温湿度物联网监测
养殖场｜养殖环境温湿度物联网监测
试点客户招募中
仓储库房
库房与冷库温湿度报警监测
仓储库房｜温湿度报警监测系统
试点客户招募中
园区
水电气能耗IoT自动抄表与异常识别
园区｜水电气能耗IoT监测
试点客户招募中
Download Free Industry Solution Whitepapers
Includes industrial equipment early warning, energy management, and smart aquaculture scenarios, with industry data and ROI estimation models.
电机电流异常？别急着换设备，可能是轴承磨损的前兆
电机电流缓慢增大往往比突发过载更危险。本文结合现场经验，拆解电流趋势分析如何帮助工厂在轴承失效前捕获信号，避免非计划停机。
为什么传统阈值告警正在拖垮你的运维团队？
超过 40% 的阈值告警是无效的。告警风暴、告警疲劳、真正风险被淹没——本文用数据和场景对比，说明为什么工厂需要 AI 告警降噪。
能耗跑冒滴漏占工厂总能耗 8%-15%，这套方法帮你定位
水电气跑冒滴漏不是在月度账单上发现的，而是在非工作时段的分表数据里。本文介绍如何通过分项计量 + 时段对比，精准定位能耗异常。
Want a Customized Solution?
Tell us your monitoring requirements, and we'll provide a one-on-one solution proposal with ROI analysis.
Request a Demo
Request a Demo, Get Your Solution Quote
Tell us about your monitoring targets and point count. We will provide access methods, sensor recommendations, and pricing estimates.
- Demo alert and dashboard effects from similar sites
- Get monitoring point recommendations and access methods based on site conditions
- Receive pricing estimates and pilot implementation timeline
Inconvenient to fill out the form? View phone and email on the contact page