GIS Indoors Presentation from the Esri UC SIG.
Quite the concept, would liked to have seen this presentation.
I'm looking for work done [algorithms if possible] for indoor navigation specifically in relation to path choice through a building ... taking into account decision criteria more than just distance ... hope you can point me in the right direction.
Did you check out the online presentation that goes into details on routing?
Indoor Location, Tracking, and Routing | Esri Video
at 34 minutes you will get the part from Robert G. who explains the routing setup. the algorithms are based on our route solver with shortest (or more accurately, least cost) path.
Does that help?
Excellent thank you … this will indeed give me a firm start.
Have a great day!
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I have now had a quick look at the presentation and got stuck at the InfSoft presentation by Herr Donaubauer … the work InfSoft has already done got me very excited … I’ll just be reinventing the wheel if I attempted to set up indoor routing routines myself … InfSoft work fits well with my current project.
It may well be that I am being a little too forward … however, is it possible for you to place me in contact with Herr Donaubauer?
For information my LinkedIn profile may be viewed here : https://www.linkedin.com/pub/william-h-hall/6/294/2b8
Although I hold a professional position in the food industry here in South Africa I have two other passions : Mountain Biking and informal Mobile App development .
Recently I set myself the task of designing an App for indoor navigation using BLE beacons … futuristically with seamless integration with Google Earth i.e. from street level GPS to indoor locations.
Your assistance will be most appreciated.
.. and perhaps I should also have mentioned that my specific interest is to assist the visually impaired to navigate unfamiliar indoor structures … from hotels to government buildings. I have played a little with Dijkstra’s algorithm but its perhaps too basic for route decisions based on a one “cost” attribute … I extended this a little by playing with a “cost-coefficient” made up of weighted sub-costs … in this case walking surface difficulty, propensity of ‘dangerous’ obstacles and difficulty of interaction . As the visually impaired cannot access visual data both on App or environment I had to build these into a voice interaction with the App … and using environment descriptors in service of the tactile, smell and sound senses …
I hope this explanation gives a little more information of my quest.
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