Determine Non-Passenger Data from WiFi Scanner Data (MAC Address), A Case Study: Romango Bus, Obuse, Nagano Prefecture, Japan

Hidayat, Arief; Terabe, Shintaro; Yaginuma, Hideki

doi:10.14246/irspsda.6.3_154

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…A few pasts ponders have utilized Wi-Fi scanners for transport travellers [14,15], paratransit travellers [16], and utilized people on foot [17]. A Wi-Fi scanner can stack all MAC address information into a log record.…”

Section: Equipmentmentioning

confidence: 99%

Street Crowdedness and Urban Congestion Level by MAC and GPS Data

Hidayat

2024

IOP Conf. Ser.: Earth Environ. Sci.

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Wi-Fi is one of the emerging technologies today. Wi-Fi refers to MAC (Media Access Control) address data. A MAC address represents a device number. In other words, it represents the number of people. The system uses MAC address data to determine road traffic congestion and land use, detects the number of terminals using a Wi-Fi scanner, and analyzes vehicle speed using GPS. The purpose of this research is to understand city-level services from traffic services and road congestion status and degree of congestion using Wi-Fi data (MAC addresses). This method was used for this study by providing a Wi-Fi scanner and a GPS scanner inside the bus. A Wi-Fi scanner that collects MAC address data and GPS for calculating bus speed. The congestion hypothesis in this study is that the bus is slow, and the total number of MAC addresses is high at the same time, or vice versa. The results show that the maximum correlation value between speed and total number of MAC addresses is -0.629. Negative correlation leads to slower bus speeds, higher total MAC addresses, and different. The numbers indicate the congested sections around the bus route during the bus operating hours. Several parameters such as travel time, travel speed and standard deviation/variance were analyzed for congestion level. Analyze aspects that link road conditions to good or bad service. Congestion levels can be determined based on RI, which is derived from the standard deviation and average speed of each road link.

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Section: Equipmentmentioning

confidence: 99%

Street Crowdedness and Urban Congestion Level by MAC and GPS Data

Hidayat

2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…According to Ikram and Qamar (2015), the system provides users with results, recommendations, and explanations. In the rule-based expert system (Figure 3), the knowledge is used as the basis of the problem-solving procedures (Hidayat, Terabe, et al, 2018). A rule can reason about the characteristics of a frame by referring to its slot values (Purwohandoyo, Reinhart, et al, 2023).…”

Section: Parameter Decisionmentioning

confidence: 99%

Suitable Potential Locations for Street Vendors in Makassar City, Indonesia

Akil

ユドノ

Osman

et al. 2023

IRSPSD International

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Recently, both the Makassar city government and its residents have encountered difficulties in anticipating and managing street vendors, due largely to unclear policies regarding location regulation. Meanwhile, the proliferation of street vendors has led to the occupation of unplanned trading areas, resulting in increased traffic congestion and a decline in the quality of the urban environment. The presence of street vendors should ideally contribute to the city's mosaic, shaping the city's image and serving the community's needs, including tourists. This article attempts to address the pressing issues surrounding the creation of a productive and liveable city. The purpose of this study is to develop a model for suitably locating street vendors in Makassar. This article identifies various supportive and inhibiting parameters and subsequently develops them into rules for spatial analysis. These parameters were gathered through interviews with traders, community members, and government officials, and the data was structured using expert choice techniques. Each weighted parameter was used to assess the grid-based land surface using the ArcGIS program. The article proposes a model for suitably locating street vendors, which can be applied to cities similar to Makassar. As a result of spatial data input to the model, potential locations in three districts were identified, falling into three categories. In general, Category 1 comprises 114 grids of the high suitability potential locations that nearly meet all the principles of suitable street vendor workplaces, among 1164 grid locations. Category 2 represents suitable potential locations, and Category 3 denotes low suitability potential locations.

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“…By default, network cards are set to normal scan mode. If the host wishes to scan all passing network frames from the wireless networks, its network card needs to be set in Promisc (monitor mode) [1,11,13,16,17,21,22,25,30,31,33]. All wireless networks work in infrastructure mode and in this regard every wireless network device sends special beacon network frames which broadcast SSID information to all nearby wireless devices.…”

Section: Introductionmentioning

confidence: 99%