Hey July tomonidan Holosentinel Aqlli Hamjamiyat Tizimi

Hey July tomonidan yaratilgan Holosentinel Aqlli Hamjamiyat Tizimi — Axborot Texnologiyalari Dizayni tanlov toifasida nufuzli 2025 A' Design Award Kumush Mukofoti mukofotining yuqori baholangan g'olibidir.

KumushAxborot Texnologiyalari· 2025

Holosentinel Aqlli Hamjamiyat Tizimi

muallif: Hey July

Mijoz: Hey July

Axborot Texnologiyalari toifasida A' Design Award Kumush Mukofoti g'olibi

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A' Design Award saytida ko'rish Press-reliz Mukofot nishoni

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Holosentinel Aqlli Hamjamiyat Tizimi haqida

Gibrid 3D tizim aerokosmik darajadagi aniqlikni intuitiv boshqaruv elementlari bilan birlashtiradi. 3D qatlamlar bino tuzilmalari va dinamik xavflarni vizualizatsiya qiladi, 2D panellar esa issiqlik kodlash orqali energiya iste'moli va qurilma ishlashini kuzatadi. AI xulq-atvor modellari yuqori xavfli hududlarni avtomatik aniqlaydi va hodisalarni besh soniya ichida lokalizatsiya qilish imkoniyatini beradi. Fazoviy algoritmlar 3D olomon issiqlik xaritalari orqali HVAC va yoritishni optimallashtirib, energiya sarfini 30 foizga kamaytiradi. Imo-ishoralarga asoslangan navigatsiya makro va mikro ko'rinishlar o'rtasida uzluksiz o'tishlarni ta'minlab, interfeys bilimi va operatsion samaradorlikda muhim yutuqlarga erishadi.

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A' Design Award Kumush Mukofoti haqida

Holosentinel Aqlli Hamjamiyat Tizimi A' Design Award Kumush Mukofotining g‘olibi bo‘lib, bu go‘zal, ulug‘vor va ta’sirchan eng yuqori darajadagi dizaynlarga beriladigan favqulodda nufuzli e’tirofdir. Kumush g‘oliblari o‘z dizaynerlarining ajoyib mahorati, iste’dodi va o‘tkirligini ko‘rsatuvchi juda yorqin va o‘ta ijodiy asarlardir. Holosentinel Aqlli Hamjamiyat Tizimi ajoyib, namunaviy, diqqatga sazovor darajada kasbiy va chuqur innovatsion asar bo‘lishi kutiladi. A' Design Award Kumush Mukofotini qo‘lga kiritgan ushbu dizayn san’at, fan, dizayn va texnologiya chegaralarini kengaytiruvchi juda e’tiborga loyiq, tahsinga sazovor ixtirodir. Holosentinel Aqlli Hamjamiyat Tizimi ko‘pchilik havas qiladigan, istaklarni uyg‘otadigan, ijobiy tuyg‘ular olib keladigan hamda hayrat va ajablanish uyg‘otadigan ijoddir.

Dizayn ortida

Press-kit

Dizayner tomonidan taqdim etilgan kreditlar, jamoa a'zolari va texnik tafsilotlar.

Noyob xususiyatlar: 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.
O'lchamlar va qadoqlash: 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.
Teglar: Digital Twin Community Safety, 3D Visualized Security Intelligence, Vulnerable Group Spatial Protection, Millimeter-Accurate Energy-Saving Modeling, Cross-Dimensional Cognitive Interface
Ishlab chiqarish texnologiyasi: 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.
Dizayn muammosi: 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.
Tadqiqot: 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.
Ilhom: 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.
Loyiha muddati: Development Began in September 2022, Followed by Pilot Testing in a Residential Community in Beijing. The System Was Successfully Deployed in January 2023.
Ish jarayoni: The System Supports Both Mouse and Tablet Touch Controls, Allowing Users to Navigate 3D Spatial Models, Access Operational Features, and Conduct Precise Searches Seamlessly.
Jamoa a'zolari: Leader: Gao Chao
Technical Consultant: Bao Xiaopan
Designer: Zhang Shiqi
3D Modeler: Fan Shengming
Development Engineer: Wang Qi
Rasm mualliflari: 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.