Mapping of MAC Address with Moving WiFi Scanner

Recently, Wifi is one of the most useful technologies that can be used for detecting and counting MAC Address. This paper described using of WiFi scanner which carried out seven times circulated the bus. The method used WiFi and GPS are to counting MAC address as raw data from the pedestrian smartphone, bus passenger or WiFi devices near from the bus as long as the bus going around the route. There are seven processes to make map WiFi data

Mapping of MAC Address with Moving WiFi Scanner

Recently, Wifi is one of the most useful technologies that can be used for detecting and counting MAC Address. This paper described using of WiFi scanner which carried out seven times circulated the bus. The method used WiFi and GPS are to counting MAC address as raw data from the pedestrian smartphone, bus passenger or WiFi devices near from the bus as long as the bus going around the route. There are seven processes to make map WiFi data

WIFI SCANNER FOR OBTAINING PEDESTRIAN DATA

Recently, many technologies to estimate pedestrian data to know about pedestrian travel behavior. Wifi is one of the most useful technologies that can be used in counting pedestrian data. This paper described using of WiFi scanner which carried out seven times circulated the bus. The method used WiFi and GPS are to counting MAC address as raw data from pedestrian smartphone or WiFi devices nearfrom the bus as long as the bus going around the route, generate and processing to be pedestrian data. There are five processes to make pedestrian data from raw data. The purpose of this study is to calculate, obtain and estimate the number of pedestrian data divide circulation number and road segmentation.

(Section A: Planning Strategies and Design Concepts)

WiFi is one of the most useful technologies that can be used for detecting and counting MAC addresses. Many previous studies have interpreted MAC address data into other forms for use in infrastructure development and urban transport. This study uses onboard WiFi scanners, circulated on the "Romango Bus", a hop-on-hop-off bus that has nine bus stops with roaming time from 09.50 to 17.50. The method uses WiFi and GPS MAC addresses as raw data from WiFi devices, collected during the time the bus goes around the route. WiFi scanner devices are placed on two different buses for comprehensive monitoring of the route\u27s operating hours. Raw data obtained in the form of WiFi data and GPS data is combined and processed through five steps to produce non-passenger data. The results are displayed on a map that contains MAC address data, and that specifies non-passenger data categorized into pedestrians, vehicles, and buildings. Obuse is a tourist area that has many tourist attractions, and the results of WiFi at stopover locations shows a high number of pedestrians, especially at Obuse Park and Obuse Station

Planning and Designing Walkable Cities: A Smart Approach

Walking may be considered one of the most sustainable and democratic ways of travelling within a city, thus providing benefits not only to pedestrians but also to the urban environment. Besides, walking is also one of the means of transport most likely subjected to factors outside an individual\u2019s control, like social or physical abilities to walk and the presence of comfortable and safe street infrastructures and services. Therefore, improving urban conditions provided to pedestrians has positive impacts on walkability. At the same time technological solutions and innovations have the power to encourage and support people to walk by overcoming immaterial barriers due to a lack of information or boring travel and they give to decision makers the possibility to gain data to understand how and where people travel. Merging these two dimensions into a unique approach can drastically improve accessibility, attractiveness, safety, comfort and security of urban spaces. In this context, this paper aims to draw a more multifaceted context for walkability, where new technologies assume a key role for introducing new approaches to pedestrian paths planning and design and thus for enhancing this mode of transport. Indeed, by combining more traditional spatial-based and perceptual analysis of the urban environment with technological applications and social media exploitation there will be room to better support the decision on and to enhance satisfaction of walking as well as to easier plan and design more walkable cities

Contextual Adjustment of the ITE Trip Generation Rates Using Wi-Fi and Bluetooth Technologies

The ITE Trip Generation Handbook has been in common use for about half a century to estimate vehicle trips generated by more than 172 land use categories as a function of establishment size (floor area) only. However, observed trip rates display a huge error range across different sites. Although contextual adjustment factors can ameliorate the error in the ITE trip generation estimates considerably, local site-specific trip generation rates should be collected for this purpose. Due to the huge time and monetary costs of data collection, adjusting the ITE trip generation rate is ignored by many jurisdictions. The primary contribution of this research is the theoretical development of an automated vehicle counting method at individual land uses using Wi-Fi and Bluetooth detections for the first time as a part of establishing the impact of contextual adjustment factors to the ITE trip generation rates. In this study, data was collected by both conventional and alternative methods for strip mall land use category across six parishes of Louisiana state and then compared to each other to develop contextual adjustment factors for the given land use category across the study area. The results of this study show that floor area and built environment factors explain about half of the trip rate variation observed in Louisiana and therefore it is suspected that there are still other factors that should be taken into account before accurate estimates of trip rates can be obtained. The automated data collection method using Wi-Fi and Bluetooth detections produces estimates that correlate with observed values with correlation coefficients that vary between 0.6 and 0.8

Pedestrian and Bicycle Data Collection System in Rovaniemi

Diplomityön tarkoituksena on luoda toimintasuunnitelma jalankulku- ja pyöräliikenteen tiedonkeruujärjestelmän kehittämiseksi Rovaniemen kaupungissa. Työ on osa Rovaniemen kaupungin tilaamaa projektikokonaisuutta, jossa selvitetään kaikkien liikennemuotojen laskennan automatisoinnin mahdollisuutta. Työ koostuu kirjallisuusselvityksestä, haastattelututkimuksesta ja tapaustutkimuksesta, joiden avulla tutkimusongelmaan pyritään vastaamaan. Jalankulku- ja pyöräliikenteeseen liittyy monipuolisia tietotarpeita, jotka nousevat muun muassa rahoituksen, kaavoituksen, teknisen suunnittelun, kunnossapidon, päätöksenteon ja liikkujien monimuotoisista tarpeista. Liikennetiedon käyttökohteiden ollessa monipuolisia ja laajoja on selvää, että tarvittava liikennetieto täytyy olla monimuotoista käyttökohteestaan riippuen. Ei ole mahdollista määrittää esimerkiksi tarkkoja tunnuslukuja, joita kävely- ja pyöräliikenteestä tulisi aina mitata vaan tunnuslukujoukko on valittava tarvekohtaisesti sekä myös kaupungin kiinnostuksen kohteiden mukaan. Liikennetiedon keruu on perinteisesti luokiteltu liikennelaskentoihin, liikkumiskyselyihin ja havainnointitutkimuksiin. Tekniikan kehittyessä tämä jaottelu on kuitenkin katoamassa kun yhdellä menetelmällä voidaan kerätä tietoa, joka sopii kaikkiin edellä mainittuihin kategorioihin. Diplomityön rajallisuuden vuoksi työssä kuitenkin keskitytään vain niihin menetelmiin, joilla voidaan tuottaa eritoten tietoa liikennemääristä. Nämä menetelmät jaotellaan työssä käsinlaskentaan, konelaskentaan ja paikannukseen perustuviin menetelmiin. Lopuksi Rovaniemen kaupungille luodaan toiminta suunnitelma jalankulku- ja pyöräliikenteen tiedonkeruujärjestelmän kehittämiseksi. Toimintasuunnitelma koostuu tunnuslukujoukon koostamisesta, laskentapisteiden määrittelemisestä, laskentamenetelmien valinnasta sekä toteutusaikataulun luomisesta.The object of this Master’s Thesis is to create an action plan in order to develop the pedestrian and bicycle data collection system in the city of Rovaniemi. The work consists of literature review, interview surveys, and a case study. Developing pedestrian and bicycle traffic system generates diverse information needs which generally evolve around the needs of land use planning, technical planning, street maintenance, financing, decision making, and the users of traffic – people. Since the application of traffic information is versatile it is self-evident that the information itself must be diverse according to the needs of the user. Therefore, it is not possible to define specific pedestrian or bicycle traffic key indicators which should always be measured. Instead, the key indicators should be chosen independently for every project keeping in mind the need and interests of the information user. Traditionally traffic data collection has been classified into three classes: traffic counts, traffic surveys, and observation surveys. Recently, the development of technology has made this classification more and more obsolete. Nowadays we can use technological solutions which could collect data typical to all of the classes mentioned above. Nevertheless, only methods that would traditionally be considered as traffic counting methods are considered here, due to the limit of Master’s Thesis extent. These methods are classified as manual counts, automatic counts and counts based on tracking of people. Finally, an action plan to develop the pedestrian and bicycle data collection system is created for Rovaniemi. The action plan consists of compiling a set of key indicators, defining data collection points, selecting appropriate data collection method, and designing an implementation schedule