人工智能+工具方案目录

WISIO 是一款智能多媒体（相片和影像）AI 分析和模型管理系统，提供端到端解决方案的无程式码平台，用于建立和部署行业特定的视觉 AI 模型。它能无缝整合资料、训练模型并进行智能识别，赋能资料驱动的决策，同时大幅降低技术门槛和成本。

无需 AI 专业知识，让使用者也能有效率地管理整个模型的生命周期，从而获得新的营运洞察，并提升各种应用的生产力。

WISIO is an intelligent multi-media (image and video)， AI analysis and model management system that provides an end-to-end, no-code platform for building and deploying industry-specific vision AI models. It seamlessly integrates data, trains models, and performs intelligent identification to empower data-driven decision making, all while drastically reducing technical barriers and cost.

This allows users without AI expertise to efficiently manage the entire model lifecycle, unlocking new operational insights and driving productivity across a wide range of applications.

全面的智能视觉AI管理系统透过自动化劳动密集和关键监控任务，大幅提升公共服务水准并降低营运成本。例如，它可以透过城市车辆行车记录器自动识别基础设施缺陷，例如坑洞、人行道开裂或路牌损坏，从而在问题恶化和成本上升之前主动进行修复，从而提升公共安全并延长资产使用寿命。在公共卫生和安全领域，它可以分析闭路电视录像，检测公共区域过度拥挤、无人看管的行李或跌倒等异常情况，从而加快紧急应变速度。

此外，它还透过快速分析图片和影像寻找违规行为，简化了从公立学校食品安全到环境监测等合规性检查流程，使有限的检查人员能够专注于最高优先顺序的案件。这种自动化技术减少了对人工重复监控的需求，并实现了从昂贵的被动维护转向高效、数据驱动的主动管理，从而达致成本节约，同时提供更安全、更可靠、更高质素的公共服务。

A comprehensive intelligent vision AI management system significantly improves public service and reduces operational costs by automating labor-intensive and critical monitoring tasks. For instance, it can automatically identify infrastructure defects like potholes, cracked sidewalks, or damaged street signs from city vehicle dashcams, enabling proactive repairs before problems worsen and become more expensive to fix, thereby enhancing public safety and extending asset lifespans. In public health and safety, it can analyze CCTV footage to detect anomalies like overcrowding, unattended bags, or falls in public areas, triggering faster emergency response times.

Furthermore, it streamlines regulatory compliance inspections—from food safety in public schools to environmental monitoring—by quickly analyzing images and videos for violations, allowing a limited inspector workforce to focus only on the highest-priority cases. This automation directly translates into massive cost savings by reducing the need for manual, repetitive monitoring and enabling a shift from costly reactive maintenance to efficient, data-driven proactive management, all while delivering a safer, more reliable, and higher-quality public service.