Holosentinel 智慧社区系统 by Hey July is a highly esteemed winner of the very prestigious 2025 A' Design Award 银奖 in 信息技术设计 Competition Category.

银信息技术· 2025

Holosentinel 智慧社区系统

by Hey July

Client: Hey July

A' Design Award 银奖 Winner in 信息技术 Category

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Verified Award Winner

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View at A' Design Award Press Release Award Badge

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The Design

About Holosentinel 智慧社区系统

混合3D系统结合航天级清晰度与直观操控。3D图层可视化建筑结构和动态风险，而2D面板采用热力编码监测能源使用和设备性能。AI行为模型自动标记高风险区域，实现五秒内事件定位。空间算法通过3D人群热力图优化暖通空调和照明系统，降低30%的能源消耗。基于手势的导航确保宏观与微观视图之间的无缝切换，在界面认知和操作效率方面实现突破。

The Recognition

About the A' Design Award 银奖

Holosentinel 智慧社区系统是 A' Design Award 银奖得主，这是授予顶级、华美而令人印象深刻的设计的极为崇高的认可。银奖得主是极其卓越、极具创造力的作品，展现出其设计师杰出的专业技能、才华与敏锐。预计Holosentinel 智慧社区系统将成为一件出色的典范之作，兼具非凡的专业性与深刻的创新性。这件赢得 A' Design Award 银奖的设计是一项备受瞩目、令人钦佩的发明，造福并拓展艺术、科学、设计和技术的边界。Holosentinel 智慧社区系统是一件令人羡慕的创作，它唤起渴望，带来积极的情感，并激发惊叹与赞叹。

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: Featuring a hybrid 2D and 3D interface with aerospace-grade clarity, the system offers an intuitive spatial view. The 3D layer highlights structures and risks like stalking alerts, while 2D panels show real-time energy and device status via thermal coding. Users can tap floor plans for details or swipe to shift views. AI-driven models detect high-risk zones, enabling five-second security responses. Spatial optimization cuts energy use by 30 percent, enhancing both visual cognition and operational intelligence.
Dimensions & Packaging: The System Is Compatible With Mainstream 16:9 Screen Ratios (e.g., 1920 x 1080, 3840 x 2160), Ensuring High-Clarity 3D Visualization Across Various Devices While Maintaining Spatial Accuracy.
Tags: Digital Twin Community Safety, 3D Visualized Security Intelligence, Vulnerable Group Spatial Protection, Millimeter-Accurate Energy-Saving Modeling, Cross-Dimensional Cognitive Interface
Production Technology: Utilizing precise one-to-one 3D modeling with sensor positioning accuracy of less than 2 cm, the system integrates real-time IoT data, including surveillance feeds and access logs, into its digital twin. Light and shadow physics enhance realism, while aerospace-grade mission color coding improves clarity: blue for security alerts, orange for energy issues, and a dark background for hierarchy. This design enables 0.3-second critical data recognition, ensuring seamless spatial-to-operational response.
Design Challenge: Internally, the Challenge Was to Develop a Fully Functional 3D Engine, AI Models, and UX Design Within Just Three Months. A Modular Architecture Was Implemented to Decouple the Real-Time 3D Framework From Backend Algorithms, Enabling Parallel Workflows That Reduced Development Time by 40 Percent. Externally, the Biggest Obstacle Was IoT Fragmentation Across Seven Different Protocols. To Address This, a Lightweight Middleware Was Created to Standardize Proprietary Protocols Into a Unified Data Stream. Automated Compatibility Testing Further Ensured Interoperability Among Six Major Security Brands, Effectively Bridging Ecosystem Silos.
Research: Type of Research: Applied Design Research.
Research Objectives: Validate digital twin technology for enhancing community safety and energy optimization.
Methodology: Mixed-methods integrating IoT sensor analytics with user behavior observation.
Data Collection/Tools: IoT sensor data and digital twin modeling for spatial data fusion.
Participants: 385 residents and 18 managers from a Beijing pilot community.
Results: Achieved 42% faster emergency responses and 27% reduced energy use.
Insights/Impacts: Predictive risk management redefines smart city governance, bolstering property tech, societal safety, and energy-efficient design.
Inspiration: Leveraging Cutting-Edge Digital Twin Technology, This System Reconstructs Communities With Millimeter-Accurate 3D Modeling. Its Virtual Engine Analyzes Real-Time Data From Surveillance Cameras and Access Controls, Identifying Spatiotemporal Anomalies Such as Loitering Near Children's Areas for Proactive Crime Prediction. When Prolonged Inactivity Is Detected in Elderly Residents' Homes, the System Initiates Automated 3D Location Verification. By Transforming Fragmented Data Into Actionable Spatial Intelligence, It Evolves From a Passive Monitoring Tool Into a Proactive Guardian of Community Safety.
Project Duration: Development Began in September 2022, Followed by Pilot Testing in a Residential Community in Beijing. The System Was Successfully Deployed in January 2023.
Operation Flow: The System Supports Both Mouse and Tablet Touch Controls, Allowing Users to Navigate 3D Spatial Models, Access Operational Features, and Conduct Precise Searches Seamlessly.
Team Members: Leader: Gao Chao
Technical Consultant: Bao Xiaopan
Designer: Zhang Shiqi
3D Modeler: Fan Shengming
Development Engineer: Wang Qi
Image Credits: Image #1 : Creator Gao Chao, Holosentinel, 2024.
Image #2 : Creator Gao Chao, Holosentinel, 2024.
Image #3 : Creator Gao Chao, Holosentinel, 2024.
Image #4 : Creator Gao Chao, Holosentinel, 2024.
Image #5 : Creator Gao Chao, Holosentinel, 2024.
Video Credits: Produced by Gao Chao, 2024.