MapCorrect: Automatic correction and validation of road maps using public sensing

Abstract

With the increasing proliferation of small and cheap GPS receivers, a new way of generating road maps could be witnessed over the last few years. Participatory mapping approaches like OpenStreetMap introduced a way to generate road maps collaboratively from scratch. Moreover, automatic mapping algorithms were proposed, which automatically infer road maps from a set of given GPS traces. Nevertheless, one of the main problems of these maps is their unknown quality in terms of accuracy, which makes them unreliable and, therefore, not applicable for the use in critical scenarios.To address this issue, we propose MapCorrect: An automatic map correction and validation system. MapCorrect automatically collects GPS traces from people's mobile devices to correct a given road map and validate it by identifying those parts of the map that are accurately mapped with respect to some user provided quality requirements. Since fixing a GPS position is a battery draining operation, the collection of GPS data raises concerns about the energy consumption of the participating mobile devices. We tackle this issue by introducing an optimized sensing mechanism that gives the mobile devices notifications indicating those parts of the map that are considered as sufficiently mapped and, therefore, require no further GPS data for their validation. Furthermore, we show by simulation that using this approach up to 50% of the mobile phones' energy can be saved while not impairing the effectiveness of the map correction and validation process at all.

PSense: Reducing Energy Consumption in Public Sensing Systems

“…For instance, Farrell et al [18], [19] show in their work on continuous range queries that the next GPS fix can be deferred until the earliest point in time when the mobile device could reach the boundary of the range query. In our previous work [3], [11], [20] we employ this concept to coordinate the positioning of mobile devices in specialized sensing scenarios, like object discovery or map validation. More precisely, we use information about the Euclidean distance from a mobile device to the next point that is critical for the application.…”

“…To measure the amount of energy that is consumed for communication we used the commonly used energy model [3], [23] shown in Table I. For the communication between the mobile devices and the server we assumed GPRS.…”

“…One particular field that already attracted a lot of attention in the research community (e.g. [1], [2]) is the opportunistically gathering of sensor data with mobile devices, also called Public Sensing [3], [4]. By utilizing the build-in sensing facilities of peoples' mobile devices, Public Sensing enables a cheap way of acquiring sensor data without the need for a costly sensor deployment.…”

A Sensor Network Abstraction for Flexible Public Sensing Systems

“…MapCorrect [22] presents a system for automatic validation and correction of road maps from GPS fixes. A gateway uses a pessimistic algorithm to estimate when nodes should take GPS fixes, thus reducing the number of redundant sensor readings.…”

A novel localization and coverage framework for real-time participatory urban monitoring

“…Similar to monitoring environmental or urban scenarios with Wireless Sensor Networks (WSNs), a network of smartphones can be conceived for such tasks where a smartphone is treated as a location-aware multi-modal sensor node, and participates in the data collection process by sampling the required sensor. The notion of sensory data collection through the participation of a group of smartphone users to create knowledge is known as participatory sensing [8][9][10][11][12] in general.…”