{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/46003"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/46003","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"iNav : a hybrid approach to WiFi localization and tracking of mobile devices","abstract":"This thesis presents iNav - a hybrid system for 802.11-based localization targeted at low-power mobile devices. WiFi localization enables numerous location-based services and applications without requiring a separate GPS module, thus offering device cost and power consumption savings. iNav is a WiFi localization system targeted at low-power mobile devices, capable of utilizing multiple data sources to produce location estimates with accuracy higher than that of pure WiFi estimates. iNav uses a stochastic location estimation algorithm based on particle filters to integrate streams of WiFi access point observations and 3-axis accelerometer data. The system is tailored towards localization of vehicles and relies on a road network map to increase localization accuracy. iNav is designed with low-power devices in mind, and is capable of computing real-time location estimates on embedded devices like the iPhone.","abstract_html":"This thesis presents iNav - a hybrid system for 802.11-based localization targeted at low-power mobile devices. WiFi localization enables numerous location-based services and applications without requiring a separate GPS module, thus offering device cost and power consumption savings. iNav is a WiFi localization system targeted at low-power mobile devices, capable of utilizing multiple data sources to produce location estimates with accuracy higher than that of pure WiFi estimates. iNav uses a stochastic location estimation algorithm based on particle filters to integrate streams of WiFi access point observations and 3-axis accelerometer data. The system is tailored towards localization of vehicles and relies on a road network map to increase localization accuracy. iNav is designed with low-power devices in mind, and is capable of computing real-time location estimates on embedded devices like the iPhone.","abstract_has_math":false,"creators":["Popov, Lev, M.Eng. Massachusetts Institute of Technology"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Samuel Madden."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:21:17Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/46003","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Samuel Madden."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."]},{"key":"dc:creator","label":"Author","values":["Popov, Lev, M.Eng. 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