Knowledge Platform

Geolocation services for travel routing

Travel and tour planning is a process that involves searching, selecting, grouping and sequencing destination related products and services including attractions, accommodations, restaurants, and activities. Location-based services focus on providing information based on users’ current positions. Based on travellers’ current location and time, as well as personal preferences and needs, location services make recommendations regarding sightseeing spots, hotels, restaurants, and packaged tour plans. Location based services are quickly gaining popularity due to affordable mobile devices and ubiquitous Internet access. Websites like Foursquare, Gowalla, Google Latitude and Facebook show that people want to share their location information and get accurate location recommendations at any time and place. In return for sharing their location data, users can be matched to products, venues, events or local social relations and groups. 

Accurate predictions of the user’s preferred locations can simultaneously aid the user itself, advertisers of products specific to the recommended place and service providers (e.g. transportation to the recommended location). To provide these recommendations, location based services needs to have an accurate way to find similarities between locations or people. 

Geolocation is the determination of the physical location of an object (for example a mobile device, a laptop etc.) using various technological methods such as Global Positioning System (GPS), Radio Frequency (RF) location methods, etc. Common uses of Geolocation systems are: 
 Detecting Points of Interest (POI) on users’ maps. In case of traveling and tourism, POIs can be museums, monuments, entertainment places, etc. Geolocation systems detect users’ location and then they assist them in selecting a POI, based on proximity, and then provide navigation services. 
 Making annotations based on location. Users can express themselves either by providing comments, or photos, or videos, etc. Geolocation systems detect users’ position and combine users ‘actions with their location. These annotated media can be analyzed in further, to discover places with high popularity, common routes, favourite POIs, etc. 
 User navigation. 
 User notification about local information based on users’ location.
 Geolocation techniques 
The techniques that are used, are divided in four categories: Proximity methods, Triangulation methods, Dead Reckoning and Fingerprinting [1], [2]. 
Proximity based methods usually consists of a wireless sensor network which is divided into clusters. The location of each cluster is known. In proximity methods, each user (through his terminal) sends a signal to each cluster’s head node, and becomes assigned to the nearest cluster. The user location approximately corresponds to the location of the cluster that he/she is assigned to. This method has the drawback that large range of cluster’s head node corresponds to lower accuracy. 
Triangulation method consists of a wireless sensor network as well. In this method each user sends a signal to several network’s nodes, and then receives the signals back with altered strength and in different times. According to triangulation methods, the user calculates his relevant position to the network’s position. The three most common methods are: (a) the Angle Based Localization, (b) the Range Based Localization and (c) the Distance Based Localization
 Angle based localization uses the angle of the received signals in order to calculate each user’s orientation and distance to the cluster’s head. This method, although it is more accurate than the previous one, it is much more expensive because it requires special antennas.
 Range based Localization uses the range (signal strength or time of signal’s arrival to users’ terminal) in order to calculate users’ orientation and distance to the cluster’s head. This method consists of three approaches based on the kind of metric it uses (signal strength or signal’s time of arrival): (a) the Received Signal Strength Indicator (RSSI), (b) the Time of Arrival (ToA), and (c) the Time Difference of Arrival (TDoA). Range based techniques have the drawback that accuracy is significantly influenced by link reliabilities and noise interferences.
 Distance based Localization uses the hop distance between the sender and the receiver node in order to estimate the relevant location of user, compared to the cluster’s node location. However, accuracy in this method is reliable only if the network is dense.
 Dead Reckoning (DR) methods make predictions of users’ location based on previous estimated users’ position. These methods do not use any other external information source (e.g. Signal from network nodes), but depend on users’ terminal’s built-in sensors such as gyroscopes, accelerometers etc. This method however suffers from accumulative accuracy error which comes from the accumulation of insignificant sensor measurements’ errors.
 Fingerprinting methods aim to collect (via built-in sensors, antennas, cameras, etc.) features of the environment that are distinctive for the location and orientation of the user, and then match these features (fingerprints) to known fingerprints in order to determine user’s location and orientation. These methods do not require any external or specialized hardware other than the built – in hardware of mobile terminals. However, these methods depend highly on environmental features which must be maintained and updated constantly for each location. 

Technologies used in Geolocation: The most prominent state – of – the art technologies used for geolocation are the following:
 Global Positioning System (GPS) [3] is the most used technology for outdoor localization. GPS provides continuous positioning and timing information. Because it serves an unlimited number of users as well as being used for security reasons GPS is a one way ranging passive system. That is only users can receive the satellite sites [4]. Although for outdoor localization this technology is satisfying, it is inefficient in environments with large obstacles or indoor locations because the electromagnetic waves transferred between satellites and indoor receiver are attenuated by the buildings and the outdoor obstacles. 
 Infrared Radiation (IR) positioning systems are based on line-of-sight devices that use infrared radiation for communication. This technology is usually used for indoor localization for detecting or tracking objects or persons and is available in mobile phones, PDAs, TVs, etc. The main advantage of this technology is that it is small and lightweight. However, this technology has the following disadvantages: it demands line – of – sight, it has security and privacy issues and it is highly influenced by fluorescent light and sunlight [5], [6]. 
 Radio frequency positioning systems are based on radio waves which have the advantage of being capable to penetrate obstacles like building walls and human bodies. These systems are used for a variety of sizes of coverage areas, depending on the frequency of radio waves. As a result, we have narrow band RF systems (RFID, Bluetooth, WLAN and FM) and wide band systems. Moreover, there is the ZigBee technology which provides solutions for short and medium range communications [7]. 
 Ultrasound positioning systems are based on ultrasound waves, which imitate the bats’ perception system. These systems use ultrasound signals to estimate the position of the emitter tags from the receivers. These systems have low level accuracy and suffer a lot of interference from reflected ultrasound signals [8].
 Inertial measurement positioning systems are based on measures of velocity, orientation and gravitational forces using a combination of accelerometers and gyroscopes and sometimes magnetometers. These systems although they are independent of any external hardware and signal, they suffer from accumulated error, because for each location estimation it is added small errors due to measurements, which however accumulate and lead to larger errors after several estimations. As a result these systems demand that after some estimations, the system must acquire (using another method apparently), a correct measurement of location which resets the position and error values.
 Hybrid methods [9]: Combination of the above mentioned technologies in order to reduce each one’s disadvantages and enhance their advantages. 
Commercial Geolocation solutions

Apple, Google and Microsoft are the prevailing tech players in localization and navigation technologies, which have implemented hybrid systems that are mainly a combination of GPS (outdoor), Wi-Fi/WIMAX and Bluetooth technologies. Moreover, in indoor localization there are companies that are dedicated to a specific technology: 
 Locata: Australian company that offers beacons that send out signals that cover large areas and can penetrate walls.
 Nokia: They use beacons that send out Bluetooth signals 
 Navizon, Skyhook, TruePosition: use Wi-Fi technology 
 ByteLight: They use flickering light patterns from a LED light transmitter, and a terminal receiver (camera on a mobile phone) reads the pattern and sends it to a server where it is compared to other light fingerprints in order to find a match.
 IndoorAtlas: Their devices survey buildings for their internal magnetic cap which corresponds to a fingerprint for each location and orientation. 


[1] Zahid Farid, Rosdiadee Nordin, and Mahamod Ismail, “Recent Advances in Wireless Indoor Localization Techniques and System,” Journal of Computer Networks and Communications, vol. 2013, Article ID 185138, 12 pages, 2013. doi:10.1155/2013/185138 
[2] Zahid Farid, Rosdiadee Nordin, and Mahamod Ismail, “Recent Advances in Wireless Indoor Localization Techniques and System,” Journal of Computer Networks and Communications, vol. 2013, Article ID 185138, 12 pages, 2013. doi:10.1155/2013/185138 
[3] F. Seco, A. R. Jiménez, C. Prieto, J. Roa, and K. Koutsou, “A survey of mathematical methods for indoor localization,” in Proceedings of the 6th IEEE International Symposium on Intelligent Signal Processing (WISP '09), pp. 9–14, August 2009. 
[4] Introduction to GPS. The Global Positioning System. Ahmed El-Rabbany. Artech House. 
[5] J. Xiao, Z. Liu, Y. Yang, D. Liu, and H. Xu, “Comparison and analysis of indoor wireless positioning techniques,” in Proceedings of the International Conference on Computer Science and Service System (CSSS '11), pp. 293–296, June 2011. 
[6] R. Casas, D. Cuartielles, Á. Marco, H. J. Gracia, and J. L. Falcó, “Hidden issues in deploying an indoor location system,” IEEE Pervasive Computing, vol. 6, no. 2, pp. 62–69, 2007. 
[7] P. Vorst, J. Sommer, C. Hoene et al., “Indoor positioning via three different RF technologies,” in Proceedings of the 4th European Workshop on RFID Systems and Technologies (RFID SysTech '08), pp. 1–10, June 2008. 
[8] Runge, M. Baunach, and R. Kolla, “Precise self-calibration of ultrasound based indoor localization systems,” in Proceedings of the International Conference on Indoor Positioning and Indoor Navigation (IPIN '11), September 2011. 
[9] S. Zirazi, P. Canalda, H. Mabed, and F. Spies, “Wi-Fi access point placement within stand-alone, hybrid and combined wireless positioning systems,” in Proceedings of the 4th International Conference on Communications and Electronics (ICCE '12), pp. 279–284, 2012