Muundo Holosentinel Mfumo Mahiri wa Jamii na Hey July ni mshindi mashuhuri wa tuzo ya kifahari ya 2025 Tuzo ya Fedha ya A' Design Award katika Kategoria ya Mashindano ya Usanifu wa Teknolojia ya Habari.
FedhaTeknolojia ya Habari· 2025
Holosentinel Mfumo Mahiri wa Jamii
na Hey July
Mteja: Hey July
Mshindi wa Tuzo ya Fedha ya A' Design Award katika Kategoria ya Teknolojia ya Habari
Mshindi wa Tuzo Aliyethibitishwa
Thibitisha Hali ya Tuzo kwa #171198Muundo
Kuhusu Holosentinel Mfumo Mahiri wa Jamii
Mfumo wa 3D mseto huchanganya uwazi wa kiwango cha anga na vidhibiti rahisi kutumia. Safu za 3D zinaonyesha miundo ya majengo na hatari zinazobadilika, wakati paneli za 2D zinatumia usimbaji wa joto kufuatilia matumizi ya nishati na utendaji wa vifaa. Mifano ya tabia ya AI inaweka alama kiotomatiki maeneo yenye hatari kubwa, kuwezesha upatakanaji wa tukio kwa sekunde tano. Kanuni za nafasi huboresha HVAC na taa kupitia ramani za joto za umati wa 3D, kupunguza matumizi ya nishati kwa asilimia 30. Urambazaji unaotegemea ishara unahakikisha mpito laini kati ya mitazamo ya makro na mikro, kufikia mafanikio makubwa katika utambuzi wa kiolesura na ufanisi wa uendeshaji.
Utambuzi
Kuhusu Tuzo ya Fedha ya A' Design Award
Holosentinel Mfumo Mahiri wa Jamii ni mshindi wa Tuzo ya Fedha ya A' Design Award, utambuzi wenye heshima kubwa ya ajabu unaotolewa kwa miundo ya hali ya juu kabisa, ya kupendeza na ya kuvutia. Washindi wa Fedha ni kazi zinazong'aa mno na bunifu kupita kiasi zinazoonyesha utaalamu bora, kipaji na busara ya wabunifu wao. Holosentinel Mfumo Mahiri wa Jamii inatarajiwa kuwa kazi nzuri ya kuigwa ambayo ni ya kitaalamu kwa kiasi kikubwa na yenye ubunifu wa kina. Muundo huu ulioshinda Tuzo ya Fedha ya A' Design Award ni uvumbuzi unaojulikana sana na kupendwa, unaonufaisha na kupanua mipaka ya sanaa, sayansi, usanifu na teknolojia. Holosentinel Mfumo Mahiri wa Jamii ni kazi inayotamaniwa mno inayochochea hamu, huleta hisia chanya na huzua mshangao na mastaajabu.
Nyuma ya Muundo
Vifaa vya Habari
Mikopo, wanachama wa timu na maelezo ya kiufundi yaliyotolewa na mbuni.
- Sifa za Kipekee
- 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.
- Vipimo na Ufungashaji
- 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.
- Lebo
- Digital Twin Community Safety, 3D Visualized Security Intelligence, Vulnerable Group Spatial Protection, Millimeter-Accurate Energy-Saving Modeling, Cross-Dimensional Cognitive Interface
- Teknolojia ya Uzalishaji
- 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.
- Changamoto ya Ubunifu
- 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.
- Utafiti
- 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. - Msukumo
- 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.
- Muda wa Mradi
- Development Began in September 2022, Followed by Pilot Testing in a Residential Community in Beijing. The System Was Successfully Deployed in January 2023.
- Mtiririko wa Uendeshaji
- The System Supports Both Mouse and Tablet Touch Controls, Allowing Users to Navigate 3D Spatial Models, Access Operational Features, and Conduct Precise Searches Seamlessly.
- Wanatimu
- Leader: Gao Chao
Technical Consultant: Bao Xiaopan
Designer: Zhang Shiqi
3D Modeler: Fan Shengming
Development Engineer: Wang Qi - Haki za Picha
- 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.
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