6G Built-in Smart Glasses with Wifi Detection and ISAC-Supported Hierarchical Spatial Mapping
Patent Information
- Application Number
- TR202612788
- Authority / Receiving Office
- TR · TR
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2026-07-29
- Publication Date
- 2026-08-21
Smart Images
Figure 00000010_0000
Abstract
Description
1 TARIFF 6G Embedded Smart Glasses with Wifi Detection and ISAC Supported Hierarchical Spatial Navigation Mapping Technical Area 5 The invention involves 6G embedded smart glasses with wifi sensing and ISAC-supported hierarchical spatial reasoning. It is related to mapping. State of the Art Today, technologies used for the same purposes are fragmented, device-native, and not scalable. 10 Today, AR glasses that perform SLAM on phones only offer sensitivity at the meter level. It uses the phone's GPS. QR codes are used as local reference points. Each device generates its own map, and there is no sharing. Shared spatial mapping and... Time continuity cannot be ensured with this method. Cloud AR-based spatial anchoring systems, spatial map 15 created in the first session. mostly stored permanently on a central server and retrieved in subsequent sessions It is called for alignment; however, it is a constantly evolving structure with cumulative contributions from multiple sessions. It does not create a globally consistent coordinate system, hierarchical spatial order. No unified map emerges that is constantly enriched over organization or time. Classic visual-SLAM or VIO-based localization is usually achieved from the sensors of a single device. It creates a local map from the collected data. While this map can provide high accuracy, it is device-specific. And it is session-dependent; created at different times or by different users. Combining maps consistently is difficult. Furthermore, scalability over large areas is also challenging. Global referencing is limited. Although GNSS-based positioning provides global coverage, it is particularly problematic in urban canyons and 25 Accuracy decreases indoors and semantics lack spatial context. GNSS is a coordinate system. It provides the coordinates but does not model the spatial structure or objects around those coordinates; that is to say Maps don't get richer over time. Consequently, alternative methods are generally localized, single-scale, or static spatial. It produces representations. This situation makes the equipment 30 particularly useful for personnel working in complex environments. past maintenance records, sensor data, and failure probabilities directly from the physical object. This makes it difficult to see as the buildings are positioned on top of each other. Current navigation systems cannot see inside the building. It loses its validity when entered. Due to the negative aspects described above and the current solutions regarding the issue... Due to its inadequacy, it has become necessary to make improvements in the relevant technical field. 35 2 Purpose of the Invention The invention aims to eliminate the disadvantages of the existing technology and to introduce new technologies into the relevant field. Smart glasses with built-in 6G, wifi detection, and ISAC support to bring advantages. It is related to hierarchical spatial mapping. The main goal of the invention is to create 6G embedded smart glasses with wifi sensing and ISAC-supported hierarchical 5-bit architecture. The aim is to provide spatial mapping. Another aim of the invention is to enable 6G embedded smart glasses with wifi detection and ISAC support. through hierarchical spatial mapping; • in complex environments such as energy facilities, factories, infrastructure networks or transportation systems Employees can view the equipment's past maintenance records via smart glasses, sensor 10 to see the data and failure probabilities directly on the physical object. to ensure, • Thanks to hierarchical SLAM (Simultaneous Localization and Mapping), different parts of the same facility can be viewed. spatial information created by teams working in different departments is presented on a single regional map. to unify and enable all staff to use the same live spatial digital twin, 15 • Shorten maintenance times, reduce errors, and provide real-time remote expert support. to make into • Seamless positioning at street-building-room scale with 6G-enabled shared spatial mapping. to ensure, • Direction arrows, door labels, or safe route signs on the user's glasses can be physically integrated into the environment. To make it appear as if it is fixed, • data from users who previously mapped the same location in the regional SLAM layer to ensure their unification, • To offer a strong experience at airports, hospitals, shopping malls, and large campuses, • Thanks to the shared spatial cloud, different users can share the same virtual objects on the same physical 25 to enable them to see it in the location and interact with it, • design reviews, training simulations, field planning meetings, or emergency situations to provide opportunities for collaborative work in a physical space in tasks such as exercises, • From small, in-room collaborations to city-scale events with a hierarchical SLAM structure Enabling scalable, persistent AR experiences, 30 • Permanent spatial mapping at the city scale for road works, traffic regulations, and infrastructure. the direct linking of data such as locations and public information to the physical world to ensure, • municipalities or service providers, embedded in the environment seen by field personnel to enable planning and control through digital layers, 35 • To provide a highly accurate co-environment model for autonomous vehicles and robots, 3 • to harmonize human-machine spatial perception, • shared spatial awareness of teams in disaster or complex operational environments to ensure, • Regional maps created with multi-user SLAM, identifying danger zones, escape routes, and team information. Showing their locations in real time to all response personnel, 5 • Spatial guidance in environments with limited visibility (smoke, darkness, crowds) to ensure, • To enable search and rescue robots and human teams to share the same map, • Store product information, museum information, thanks to fixed reference locations in the physical world. 10. Presenting content or tourist directions attached to physical objects to ensure, • To enable the information layer to appear when the user looks through the glasses, • to ensure that the space itself becomes an interface, • To provide consistent and updatable experiences at the city scale with hierarchical mapping, • to ensure that digital content is permanently embedded in the physical world, 15 • A shared, persistent, and scalable spatial internet layer superimposed on the physical world to place, • From navigation to industrial operations, from city management to multi-user AR collaboration up to this point, the direct linking of digital information to the physical environment in every setting where humans are present. to provide, 20 • by performing the mapping process in a distributed manner across device, edge, and cloud layers to both reduce latency and increase scalability, • Eliminate dependency on a single device or single session, • by hierarchically combining multiple user and multiple session contributions Maps have become a living representation that has become richer and more accurate over time. 25 to ensure, • to ensure temporal continuity and collective learning, • Multi-scale SLAM integration enables not only local realignment but also broader areas. to enable consistent positional referencing and scene continuity, • 6G's projected high bandwidth, low latency, and network-integrated sensing / positioning 30 with its capabilities, persistent spatial content, city-scale digital twins, and constantly updated Application classes that go beyond existing AR infrastructures, such as environmental context services to support, • Thanks to the direct integration of smart glasses into the human perception-action cycle, 6G- to make it preferred in embedded XR and distributed SLAM architectures, 35 4 • By aligning the glasses' shape sensors with the user's natural line of sight (gaze level) Generating contextual information about intentions, such as what someone is looking at and what they want to interact with. • To enrich the mapping data semantically, • The glasses can provide augmented reality feedback along the same optical axis. By making the sensing-mapping-imaging chain a closed loop, 5 • To enable the system to update its behavior instantly based on user actions, • Thanks to their wearable and continuous wearable design, they enable uninterrupted data transfer across multiple sessions throughout the day. to enable the collection and cumulative map evolution among users, • Compared to a camera that only collects passive data, the glasses have a more meaningful sensor. making both the platform and an interactive XR interface 10 It was created for this purpose. Figures that will help understand the invention. Figure 1 shows a general representation of the system that is the subject of the invention. Explanation of Part References 100: Smart glasses 200: Base station 300: Wi-Fi hotspot 400: Edge calculation node 20 401: Mini point cloud 402: Visual characteristics 403: Exposure data 404: RF map data 405: Macro point cloud 25 406: Multi-modal fusion layer 407: Global SLAM optimization layer 408: Dense 3D reconstruction layer 409: Semantic fusion layer 410: Edge data and map memory unit 30 500: Regional cloud layer 600: Global cloud layer Detailed Description of the Invention In this detailed explanation, the preferred configurations of the invention are not merely for better understanding the subject. This is intended to facilitate understanding and will not create any limiting effects. The invention is based on 6G embedded technology. It relates to smart glasses with wifi detection and ISAC-supported hierarchical spatial mapping. In a preferred application of the system in question, smart glasses (100) include an RGB camera, Feature 5 includes a 6-axis IMU, low-latency wireless connectivity, and visual-inertial odometry. It has an embedded artificial intelligence processor that can run its inference. For smart glasses (100) Absolute position sensors such as GNSS, UWB, or depth sensors are not mandatory. In a preferred application of the system that is the subject of the invention, the base station (200) uses phased array MIMO beamforming, wideband echo reception, CSI+IQ access, local radar processing, and RF-SLAM. It is capable of performing reconstruction work. 10 In a preferred application of the system that is the subject of the invention, the Wi-Fi access point (300), in particular to complete the areas where no detection can be received from the base station (200) in indoor spaces It is helpful. In a preferred implementation of the system in question, the edge calculation node (400) is based on very close to the stations (200) and data from multiple users or smart glasses (100), 15 map by combining suitable base station (200) ISAC data and Wi-Fi detection data creating, sharing the relevant location map from the created map with smart glasses (100) It performs the operations. Edge calculation node (400), for smart glasses (100) optimized, low-polygon mesh, sparse landmark, RF surface, semantic anchor data. It transmits to smart glasses (100) or user equipment. 20 In a preferred application of the system that is the subject of the invention, the mini point cloud (401), smart The local 3D geometry with a radius of 1–5 m around the glasses (100) is small local geometry produced by the device. It is a point cloud. In a preferred application of the system that is the subject of the invention, visual features (402) are available in smart glasses. (100), 2D points that can be found again on images taken by RGB camera 25 It is obtained by extraction using algorithms such as FAST, ORB, Shi-Tomassi, or Harris. The detected pixel circles are matched using algorithms such as BRIEF, SIFT, or FBREAK. Feature points between frames are being identified. In a preferred application of the system that is the subject of the invention, the exposure data (403), smart glasses (100) Position information is extracted from the matching points. 30 In a preferred application of the system that is the subject of the invention, RF map data (404) is closed. Using Wi-Fi detection in locations to map gaps that ISAC cannot see It is used. In a preferred application of the system in question, the macro point cloud (405), ISAC It is a large-scale 3D point cloud generated by a supported base station (200). 35 6 In a preferred application of the system in question, the multi-modal fusion layer (406), It combines data from different sensors in a common space and time. Time Synchronization, coordinate alignment, and sensor calibration take place at this layer. In a preferred implementation of the system described in the invention, the global SLAM optimization layer (407) makes all instrument positions and the map consistent. 5 In a preferred application of the system described in the invention, a dense 3D reconstruction layer (408) produces a dense surface / mesh from sparse points. In a preferred application of the system in question, the semantic fusion layer (409), It enriches geometry with meaning. In a preferred implementation of the system described in the invention, the edge data and map memory unit is 10. (410), the resulting map or regional cloud layer (500) taken regional map It stores the edge data and map memory unit (410), such as the edge cache. is behaving. In a preferred implementation of the system that is the subject of the invention, the regional cloud layer (500), base Internet service at city / neighborhood / campus scale near station (200) 15 It is the data center of the provider (ISP). Coming from numerous edge computing units (400) Regional maps are created by combining the maps. In a preferred implementation of the system in question, the global cloud layer (600), national or performs global-scale map merging and modeling operations. Many 20 number of regional cloud layers (500) feed or are fed by this layer. In a preferred application of the system that is the subject of the invention, smart glasses (100) The sensors operate simultaneously. The RGB camera captures images. The IMU measures acceleration and angular motion. It measures. In a preferred application of the system described in the invention, triangulation, sparse 3D point local geometry, small point cloud (401) 25 with extraction and near-surface estimation is being removed. In a preferred application of the system described in the invention, light pre-processing is performed within the device. is done. Keypoint is extracted from the image. Visual features (402) are produced and The position data (403) is extracted. In a preferred application of the system that is the subject of the invention, Wi-Fi access points (300), CSI 30 It measures and performs multipath analysis. Coarse RF surface (404) is extracted. In a preferred application of the system that is the subject of the invention, the base station (200), beam sweep It does this, collects the echoes, extracts AoA / ToF / Doppler. A macro point cloud (405) is extracted. In a preferred implementation of the system in question, at the edge calculation node (400) Multi-modal fusion layer (406) time synchronization, coordinate transformation, sensor 35 Confidence weighting performs data matching operations. 7 In a preferred implementation of the system described in the invention, the global SLAM optimization layer (407) performs the positioning and mapping process. It establishes the position graph, loop It checks for closure and corrects drift. In a preferred application of the system described in the invention, a dense 3D reconstruction layer (408) produces a dense surface / mesh from sparse points. 5 In a preferred application of the system in question, the semantic fusion layer (409) AI It labels surface segments (wall, door, glass, person, object, etc.) with its models. In a preferred implementation of the system in question, the edge calculation node (400) Edge data and map memory unit (410) and map and acquisition in regional cloud layer (500) Other data collected is stored for reuse as needed. 10 In a preferred application of the system covered by the invention, at periodic intervals or as needed Updates are sent to the global cloud layer (600). In a preferred implementation of the system in question, large (600) in the global cloud layer Scaled optimization (region merging, long-term drift correction, global semantic model) (updates etc.) are being carried out. 15 In a preferred implementation of the system that is the subject of the invention, the regional cloud layer (500) and Edge computing node (400) globally optimized by global cloud layer (600) It is fed with updates. In a preferred application of the system described in the invention, when the user looks at a new area map edge calculation node (400) edge data and map memory unit (410) base 20 It is retrieved via stations (200). The map is optimized for glasses (100). is being sent. In a preferred application of the system in question, smart glasses (100) local alignment By doing so, it provides AR services. In a preferred application of the system that is the subject of the invention, 25 on smart glasses (100) The sensors operate simultaneously. The RGB camera captures images. The IMU measures acceleration and angular motion. It measures. In a preferred application of the system described in the invention, triangulation, sparse 3D point local geometry, small point cloud with extraction and near-surface estimation (401) is being removed. 30 In a preferred application of the system described in the invention, light pre-processing is performed within the device. is done. Keypoint is extracted from the image. Visual features (402) are produced and The position data (403) is extracted. In a preferred application of the system that is the subject of the invention, Wi-Fi access points (300), CSI It measures and performs multipath analysis. Coarse RF surface (404) is extracted. 35 8 In a preferred application of the system that is the subject of the invention, the base station (200), beam sweep It does this, collects the echoes, extracts AoA / ToF / Doppler. A macro point cloud (405) is extracted. In a preferred implementation of the system in question, at the edge calculation node (400) Multi-modal fusion layer (406) time synchronization, coordinate transformation, sensor Confidence weighting performs data matching operations. 5 In a preferred implementation of the system described in the invention, the global SLAM optimization layer (407) performs the positioning and mapping process. It establishes the position graph, loop It checks for closure and corrects drift. In a preferred application of the system described in the invention, a dense 3D reconstruction layer (408) produces a dense surface / mesh from sparse points. 10 In a preferred application of the system in question, the semantic fusion layer (409) AI It labels surface segments (wall, door, glass, person, object, etc.) with its models. In a preferred implementation of the system in question, the edge calculation node (400) Edge data and map memory unit (410) and map and acquisition in regional cloud layer (500) Other data collected is stored for reuse as needed. 15 In a preferred application of the system covered by the invention, at periodic intervals or as needed Updates are sent to the global cloud layer (600). In a preferred implementation of the system in question, large (600) in the global cloud layer Scaled optimization (region merging, long-term drift correction, global semantic model) (updates etc.) are being carried out. 20 In a preferred implementation of the system that is the subject of the invention, the regional cloud layer (500) and Edge computing node (400) globally optimized by global cloud layer (600) It is fed with updates. In a preferred application of the system described in the invention, when the user looks at a new area map edge calculation node (400) edge data and map memory unit (410) base 25 It is retrieved via stations (200). The map is optimized for glasses (100). is being sent. In a preferred application of the system in question, smart glasses (100) local alignment By doing so, it provides AR services.
Claims
9 REQUESTS 1. Hierarchical spatial navigation with built-in 6G smart glasses, wifi sensing and ISAC support. It is a mapping system, and its characteristic feature is; an RGB camera, a 6-axis IMU, low-latency wireless connectivity, and visual-inertial 5 with an embedded AI processor capable of running feature extraction via odometry. smart glasses (100), Phased array MIMO beamforming, wideband echo reception, CSI+IQ access, local radar processing and a base station capable of performing RF-SLAM reconstruction processing (200), especially in indoor areas where no detection can be received from the base station (200) Wi-Fi hotspot (300) which helps to complete, 10 coming from multiple users or smart glasses (100) very close to base stations (200). by combining the data with appropriate base station (200) ISAC data and Wi-Fi detection data. The system also includes Edge computing node (400), Mini point cloud (401), Visual features (402), Exposure data (403), RF map data (404), Macro point cloud (405), Multi-modal fusion layer (406), Global SLAM optimization layer (407), Dense 3D 15 Reconstruction layer (408), Semantic fusion layer (409), Edge data and map memory unit (410), Regional cloud layer (500), Global cloud layer (600) elements It includes. 25 35