{ "id": 220546, "title": "All you wanted to know about indoor navigation and you were too afraid to ask", "url": "/competitions/indoor-location-navigation/discussion/220546", "author_name": "Gabriel Preda", "post_date": "2021-02-18T18:29:12.820000", "votes": 116, "comment_count": 13, "views": 0, "content": "

Introduction

\n

Until few years ago, indoor navigation was an objective sought by many, achieved by just a few, and in some limited fields. I will review here some frequently used approaches in indoor location, some limitations of the existing methods, available development tools and resources and a small literature review.

\n

Frequently used approaches

\n

Few technical solutions are most of time used:

\n\n

Typical issues

\n

WiFi positioning systems that use signal power will be affected by such factors like closeness to a reflection wall, orientation of the device, position of the device with respect with the user body. Beacons, unless are placed in a very dense grid, will only give approximative position, and will need to combine the information from last close beacon with the navigation path estimation from integrated information from several sensors. In some of the papers in literature there is the recommendation to include in the position estimation models remote WiFi hotspots signal (which have the characteristic that, although much lower than signal from close hotspots, is less affected by such factors like orientation or position of the device relative to the user body).

\n

Available development tools and resources

\n

Here is a small list of available tools and resources for developing indoor navigation solutions:

\n\n

Literature sources for indoor positioning

\n

This is an incomplete list of paper about indoor WiFi positioning:

\n", "messages": [ { "id": 1209175, "postDate": "2021-02-18T18:29:12.820Z", "content": "

Introduction

\n

Until few years ago, indoor navigation was an objective sought by many, achieved by just a few, and in some limited fields. I will review here some frequently used approaches in indoor location, some limitations of the existing methods, available development tools and resources and a small literature review.

\n

Frequently used approaches

\n

Few technical solutions are most of time used:

\n\n

Typical issues

\n

WiFi positioning systems that use signal power will be affected by such factors like closeness to a reflection wall, orientation of the device, position of the device with respect with the user body. Beacons, unless are placed in a very dense grid, will only give approximative position, and will need to combine the information from last close beacon with the navigation path estimation from integrated information from several sensors. In some of the papers in literature there is the recommendation to include in the position estimation models remote WiFi hotspots signal (which have the characteristic that, although much lower than signal from close hotspots, is less affected by such factors like orientation or position of the device relative to the user body).

\n

Available development tools and resources

\n

Here is a small list of available tools and resources for developing indoor navigation solutions:

\n\n

Literature sources for indoor positioning

\n

This is an incomplete list of paper about indoor WiFi positioning:

\n", "rawMarkdown": "## Introduction\n\nUntil few years ago, indoor navigation was an objective sought by many, achieved by just a few, and in some limited fields. I will review here some frequently used approaches in indoor location, some limitations of the existing methods, available development tools and resources and a small literature review.\n\n## Frequently used approaches\n\nFew technical solutions are most of time used:\n\n* WiFi positioning system. This approach will use the intensity of the WiFi signal from multiple hotspots available in the indoor area. The application will need as well server connection - to receive the mapping between WiFi hotspot identifier and position of this one as well as the location map. From the combined information of power of signal and location of hotspot, the application will attempt to infer the phone location.\n\n* Beacon based technology. Installing a collection of beacons indoors will make possible to locate the phone based on identifying the closest beacon thus getting the position (with some approximation) based on the beacon positions map.\n\n* Navigation path estimation/correction from multiple sensors information fusion. For example, accelerometer, gyroscope, compass, barometer information can be integrated to be used for counting steps, evaluating orientation - as independent evaluation of the position indoor (from the last GPS position outside, or from last available WiFi or beacon spot indoor).\n\n\n## Typical issues\n\nWiFi positioning systems that use signal power will be affected by such factors like closeness to a reflection wall, orientation of the device, position of the device with respect with the user body. Beacons, unless are placed in a very dense grid, will only give approximative position, and will need to combine the information from last close beacon with the navigation path estimation from integrated information from several sensors. In some of the papers in literature there is the recommendation to include in the position estimation models remote WiFi hotspots signal (which have the characteristic that, although much lower than signal from close hotspots, is less affected by such factors like orientation or position of the device relative to the user body).\n\n## Available development tools and resources\n\nHere is a small list of available tools and resources for developing indoor navigation solutions:\n\n* https://developers.google.com/location-context (Google)\n* https://github.com/Navigine/Indoor-navigation-algorithms (Navigini)\n* https://developer.apple.com/videos/play/wwdc2019/245/ (Apple)\n* https://www.openhub.net/p/easyfloormap (EasyFloorMap)\n* https://www.indoorlocation.io/ (Mapwize)\n* https://support.google.com/maps/answer/1685827?hl=en (Google) \n\n## Literature sources for indoor positioning\n\nThis is an incomplete list of paper about indoor WiFi positioning:\n\n* [Deep Smartphone Sensors-WiFi Fusion for Indoor Positioning and Tracking](https://arxiv.org/abs/2011.10799) \n\n* [Wireless Localisation in WiFi using Novel Deep Architectures](https://arxiv.org/abs/2010.08658)\n* [A Novel Indoor Positioning System for unprepared firefighting scenarios](https://arxiv.org/abs/2008.01344) \n* [Indoor Distance Estimation using LSTMs over WLAN Network](https://arxiv.org/abs/2003.13991) \n* [Supervised and Semi-supervised Deep Probabilistic Models for Indoor Positioning Problems](https://arxiv.org/abs/1911.09906) \n* [Convolutional Mixture Density Recurrent Neural Network for Predicting User Location with WiFi Fingerprints](https://arxiv.org/abs/1911.09344) \n* [Statistical Location and Rotation-Aware Beam Search for Millimeter-Wave Networks](https://arxiv.org/abs/1812.08464) \n* [Indoor Localization Algorithm For Smartphones](https://arxiv.org/abs/1503.07628) \n* [Sensor-Aided Learning for Wi-Fi Positioning with Beacon Channel State Information](https://arxiv.org/abs/2007.06204) \n* [Improving the Performance of Deep Learning for Wireless Localization](https://arxiv.org/abs/2006.08925) \n* [BLE Beacons for Indoor Positioning at an Interactive IoT-Based Smart Museum](https://arxiv.org/abs/2001.07686) \n\n", "votes": 116 }, { "id": 1254592, "postDate": "2021-03-27T21:00:51.180Z", "content": "

Thanks! I had no idea where to start until I found this!

", "rawMarkdown": "Thanks! I had no idea where to start until I found this!", "votes": 1 }, { "id": 1231479, "postDate": "2021-03-09T02:46:51.350Z", "content": "

Thank you very much for the summary. It is a great learning resource. The clear explanation of various positioning sensors made it easy to understand working principles and models.

", "rawMarkdown": "Thank you very much for the summary. It is a great learning resource. The clear explanation of various positioning sensors made it easy to understand working principles and models.", "votes": 1 }, { "id": 1224649, "postDate": "2021-03-03T00:04:09.930Z", "content": "

Thanks for the summary!
\nEspecially, \"Typical issues\" has answers to the question I have previously had.

", "rawMarkdown": "Thanks for the summary!\nEspecially, \"Typical issues\" has answers to the question I have previously had.", "votes": 1 }, { "id": 1237571, "postDate": "2021-03-14T09:13:03.747Z", "content": "

Thanks you it's very userful for us beginner.

", "rawMarkdown": "Thanks you it's very userful for us beginner.", "votes": 2 }, { "id": 1232092, "postDate": "2021-03-09T13:36:08.833Z", "content": "

Thanks for sharing the collection of resources!

", "rawMarkdown": "Thanks for sharing the collection of resources!", "votes": 2 }, { "id": 1209818, "postDate": "2021-02-19T03:55:54.763Z", "content": "

Great summary thanks for sharing @gpreda !

", "rawMarkdown": "Great summary thanks for sharing @gpreda !", "votes": 2 }, { "id": 1278396, "postDate": "2021-04-19T20:55:41.703Z", "rawMarkdown": "", "votes": 1, "isDeleted": true }, { "id": 1244131, "postDate": "2021-03-18T17:57:20.070Z", "rawMarkdown": "", "votes": 2, "isDeleted": true }, { "id": 1244130, "postDate": "2021-03-18T17:56:52.010Z", "rawMarkdown": "", "votes": 2, "isDeleted": true }, { "id": 1226848, "postDate": "2021-03-04T23:43:23.027Z", "rawMarkdown": "", "isDeleted": true }, { "id": 1239424, "postDate": "2021-03-15T17:52:38.370Z", "content": "

Thanks a lot , very useful

", "rawMarkdown": "Thanks a lot , very useful ", "votes": 1 }, { "id": 1219987, "postDate": "2021-02-27T12:34:17.080Z", "content": "

thanks for all these resources :)

", "rawMarkdown": "thanks for all these resources :)\n" }, { "id": 1285504, "postDate": "2021-04-27T03:11:11.030Z", "content": "

Thank you very much for your guide

", "rawMarkdown": "Thank you very much for your guide" } ], "comments": [ { "id": 1254592, "author_name": "Eugene Teoh", "author_url": "", "post_date": "2021-03-27T21:00:51.180000", "content": "

Thanks! I had no idea where to start until I found this!

", "votes": 1, "replies": [] }, { "id": 1231479, "author_name": "Shivam Kalkar", "author_url": "", "post_date": "2021-03-09T02:46:51.350000", "content": "

Thank you very much for the summary. It is a great learning resource. The clear explanation of various positioning sensors made it easy to understand working principles and models.

", "votes": 1, "replies": [] }, { "id": 1224649, "author_name": "Maya Sakaguchi", "author_url": "", "post_date": "2021-03-03T00:04:09.930000", "content": "

Thanks for the summary!
\nEspecially, \"Typical issues\" has answers to the question I have previously had.

", "votes": 1, "replies": [] }, { "id": 1237571, "author_name": "LiJian1122", "author_url": "", "post_date": "2021-03-14T09:13:03.747000", "content": "

Thanks you it's very userful for us beginner.

", "votes": 2, "replies": [] }, { "id": 1232092, "author_name": "Vishal Grover", "author_url": "", "post_date": "2021-03-09T13:36:08.833000", "content": "

Thanks for sharing the collection of resources!

", "votes": 2, "replies": [] }, { "id": 1209818, "author_name": "Rob Mulla", "author_url": "", "post_date": "2021-02-19T03:55:54.763000", "content": "

Great summary thanks for sharing @gpreda !

", "votes": 2, "replies": [] }, { "id": 1278396, "author_name": "", "author_url": "", "post_date": "2021-04-19T20:55:41.703000", "content": "", "votes": 1, "replies": [] }, { "id": 1244131, "author_name": "", "author_url": "", "post_date": "2021-03-18T17:57:20.070000", "content": "", "votes": 2, "replies": [] }, { "id": 1244130, "author_name": "", "author_url": "", "post_date": "2021-03-18T17:56:52.010000", "content": "", "votes": 2, "replies": [] }, { "id": 1226848, "author_name": "", "author_url": "", "post_date": "2021-03-04T23:43:23.027000", "content": "", "votes": 0, "replies": [] }, { "id": 1239424, "author_name": "Salim Khazem", "author_url": "", "post_date": "2021-03-15T17:52:38.370000", "content": "

Thanks a lot , very useful

", "votes": 1, "replies": [] }, { "id": 1219987, "author_name": "Mnka", "author_url": "", "post_date": "2021-02-27T12:34:17.080000", "content": "

thanks for all these resources :)

", "votes": 0, "replies": [] }, { "id": 1285504, "author_name": "kzbzdnb", "author_url": "", "post_date": "2021-04-27T03:11:11.030000", "content": "

Thank you very much for your guide

", "votes": 0, "replies": [] } ], "raw_markdown_by_id": { "1209175": "## Introduction\n\nUntil few years ago, indoor navigation was an objective sought by many, achieved by just a few, and in some limited fields. I will review here some frequently used approaches in indoor location, some limitations of the existing methods, available development tools and resources and a small literature review.\n\n## Frequently used approaches\n\nFew technical solutions are most of time used:\n\n* WiFi positioning system. This approach will use the intensity of the WiFi signal from multiple hotspots available in the indoor area. The application will need as well server connection - to receive the mapping between WiFi hotspot identifier and position of this one as well as the location map. From the combined information of power of signal and location of hotspot, the application will attempt to infer the phone location.\n\n* Beacon based technology. Installing a collection of beacons indoors will make possible to locate the phone based on identifying the closest beacon thus getting the position (with some approximation) based on the beacon positions map.\n\n* Navigation path estimation/correction from multiple sensors information fusion. For example, accelerometer, gyroscope, compass, barometer information can be integrated to be used for counting steps, evaluating orientation - as independent evaluation of the position indoor (from the last GPS position outside, or from last available WiFi or beacon spot indoor).\n\n\n## Typical issues\n\nWiFi positioning systems that use signal power will be affected by such factors like closeness to a reflection wall, orientation of the device, position of the device with respect with the user body. Beacons, unless are placed in a very dense grid, will only give approximative position, and will need to combine the information from last close beacon with the navigation path estimation from integrated information from several sensors. In some of the papers in literature there is the recommendation to include in the position estimation models remote WiFi hotspots signal (which have the characteristic that, although much lower than signal from close hotspots, is less affected by such factors like orientation or position of the device relative to the user body).\n\n## Available development tools and resources\n\nHere is a small list of available tools and resources for developing indoor navigation solutions:\n\n* https://developers.google.com/location-context (Google)\n* https://github.com/Navigine/Indoor-navigation-algorithms (Navigini)\n* https://developer.apple.com/videos/play/wwdc2019/245/ (Apple)\n* https://www.openhub.net/p/easyfloormap (EasyFloorMap)\n* https://www.indoorlocation.io/ (Mapwize)\n* https://support.google.com/maps/answer/1685827?hl=en (Google) \n\n## Literature sources for indoor positioning\n\nThis is an incomplete list of paper about indoor WiFi positioning:\n\n* [Deep Smartphone Sensors-WiFi Fusion for Indoor Positioning and Tracking](https://arxiv.org/abs/2011.10799) \n\n* [Wireless Localisation in WiFi using Novel Deep Architectures](https://arxiv.org/abs/2010.08658)\n* [A Novel Indoor Positioning System for unprepared firefighting scenarios](https://arxiv.org/abs/2008.01344) \n* [Indoor Distance Estimation using LSTMs over WLAN Network](https://arxiv.org/abs/2003.13991) \n* [Supervised and Semi-supervised Deep Probabilistic Models for Indoor Positioning Problems](https://arxiv.org/abs/1911.09906) \n* [Convolutional Mixture Density Recurrent Neural Network for Predicting User Location with WiFi Fingerprints](https://arxiv.org/abs/1911.09344) \n* [Statistical Location and Rotation-Aware Beam Search for Millimeter-Wave Networks](https://arxiv.org/abs/1812.08464) \n* [Indoor Localization Algorithm For Smartphones](https://arxiv.org/abs/1503.07628) \n* [Sensor-Aided Learning for Wi-Fi Positioning with Beacon Channel State Information](https://arxiv.org/abs/2007.06204) \n* [Improving the Performance of Deep Learning for Wireless Localization](https://arxiv.org/abs/2006.08925) \n* [BLE Beacons for Indoor Positioning at an Interactive IoT-Based Smart Museum](https://arxiv.org/abs/2001.07686) \n\n", "1254592": "Thanks! I had no idea where to start until I found this!", "1231479": "Thank you very much for the summary. It is a great learning resource. The clear explanation of various positioning sensors made it easy to understand working principles and models.", "1224649": "Thanks for the summary!\nEspecially, \"Typical issues\" has answers to the question I have previously had.", "1237571": "Thanks you it's very userful for us beginner.", "1232092": "Thanks for sharing the collection of resources!", "1209818": "Great summary thanks for sharing @gpreda !", "1278396": "", "1244131": "", "1244130": "", "1226848": "", "1239424": "Thanks a lot , very useful ", "1219987": "thanks for all these resources :)\n", "1285504": "Thank you very much for your guide" } }