Department of Computer Science Assistant
Adi Shankara Institute of Engineering Department of Computer Science
and Technology,Kalady-683574 Adi Shankara Institute of Engineering
[email protected] and
CONNECTED NAVIGATION SYSTEM FOR URBAN
(IoT) has great potential to overcome existing lack of public transport
systems. The key challenge of rapidly growing cities, is to provide effective
public transportation system. To overcome these existing deficiencies,embeded
smart technologies can be applied to public transport domain. In this
paper,briefly explain about applying embedded smart technology to the public
transport domain using UBN methodology,IoT in Urban Bus Navigation(UBN) enables
navigation system for bus riders.UBN provides two major services for bus
riders.The first one is Micro-Navigation and the second one is Crowd-Aware
Micro-Navigation service helps guidance for passengers along a bus
journey by finding boarded bus vehicles and tracking progress of their journey.
The Crowd-aware route recommendation service collects & predicts crowd
levels on bus journeys that helps the bus riders to find out better,efficient
and less congusted routes. UBN system provides users with a superior awareness
of the state of the transport system and their travel options which translates
into an improved public transport experience.These all helps the peoples to get
positive impact on public transport usage and encourage public bus journey.
Internet of Things (IoT), UBN System, Micro-Navigation, Ad-Hoc Communication
With Buses, Bus Crowd Density Estimation.
of Things (IoT) is the connection of things to Internet.The IoT allows objects
to be sensed or controlled remotely across existing network infrastructure,
creating opportunities for more direct integration of the physical world into
computer-based systems, and resulting in improved efficiency, accuracy and
economic benefit in addition to reduced human intervention.The public bus transport systems have the capacity to
absorb large masses of urban travelers, their public image often suffers from a
negative perception.First, from the passenger’s view point, bus networks in
dense urban areas are often considered as complex and tough to
navigate.Second,in contrast to private modes of transport, traveling on buses
offers only a low level of comfort and least convenience. Third,bus journeys
lack a sense of personal control and ownership that is valued by car users.To
overcome these existing deficiencies,embeded smart technologies can be applied
to public transport domain.The Urban Bus Navigator(UBN),an IoT enabled
bus riders uses Micro-navigation technology and crowd aware route
recommendation methods for satisfying the needs.The UBN relies on a distributed
IoT system comprising
embedded bus computing system, backend computing infrastructure and a mobile
smartphone app to detect the
of passengers on buses and provide continuous real-time navigation over the
complete course of a bus journey.6 UBN system provides users with a superior
awareness of the state of the transport system and their travel options which
translates into an improved public transport experience. Navigation system for
bus passengers that has the ability to seamlessly interconnect bus passengers with
the real-world public bus infrastructure.All in all, UBN demonstrates the
potential of the IoT for delivering innovative urban transport experiences and
enhances the use of public transportation services.
UBN system is built upon a distributed IoT infrastructure which enables the
passenger’s smartphone devices to interact with buses in real-time and buses to
sense the presence of on board passengers6.
on these mechanisms, UBN provides two novel information services for bus passengers,they
are Micro-navigation and Crowd-aware
route Recommendation.Figure 1
refers to fine-grained contextual guidance of passengers along a bus journey by
recognizing boarded bus vehicles and tracking the passenger’s journey progress.Crowd-aware
route recommendation collects and predicts crowd levels on bus journeys to
suggest better and less crowded routes to bus riders.
Figure 1 Overview of the structure of bus journey
involves a set of distributed software and hardware components which are
tightly integrated with the bus systemFigure 2. UBN composed of 3 key
components: 1. The network-enabled urban bus system with WiFi equipped bus
vehicles. 2. The UBN navigation app for bus riders. 3. The bus crowd
information server to collect real-time occupancy information from buses
operating on different routes.
Figure 2 UBN System
Network-enabled urban bus system sense real-world bus journeys of passengers
and enable sharing of bus data with their mobile devices in an ad hoc manner.The
Crowd density estimation detects the number of passengers on a bus. For the
purpose of bus crowd density estimation,the WiFi-enabled devices carried by
passengers are periodically sending out probe requests according to their
IEEE802.11 protocol operation in order to detect the access points that are
nearby. Each vehicle deploy WiFi access point that acts as a network monitor to
continuously capture transmitted probe requests. Thus finding out the count of
passengers.The bus navigation system adds two novel components to the backend
system for making effective use of the available bus occupancy information.1)Predicting Bus Occupancy From Crowd Level
Histories,2) Least Crowded Route Recommendation.The smartphone
application for bus passengers supports real-time navigation of buses by
Another method used for urban navigation transportation
system is Novel Wireless Sensor Network Frame for Urban Transportation4.It discuss about the requirements of WSN for urban transportation
(WSN-UT) using a customized network topology.WSN-UT enables users to obtain
traffic and road information directly from the local WSN within its wireless
scope.Wireless sensor network (WSN) technologies that are low cost, low power,
and self-configuring are a key function in ITS. The potential application
scenarios and design requirements of WSN for urban transportation (WSN-UT) are
proposed in this work. A customized network topology is designed to meet the
special requirements, and WSN-UT is specifically tailored for UT applications.
WSN-UT enables users to obtain traffic and road information directly from the
local WSN within its wireless scope instead of the remote ITS data center.
WSN-UT can be configured according to different scenario requirements. A
three-level subsystem and a configuration and service subsystem constitute the
WSN-UT network frame, and the service/interface and protocol algorithms for
every subsystem level are designed for WSN-UT.
Another method is Characterizing Road Segments Using Compass
Sensors to Predict Approaching Bus Stops2.In this method it explains about
technologies that make arrival predictions through tracking vehicles in transit
through GPS provides a personalized approach via smart phone that helps users
to take advantage of sensor data to learn and personalize their bus routes, and
alert them on time when a bus stop is approaching.Two algorithms used in this
method,1) Turn detection using on-board compass sensor of a smartphone.2)
Characterizing road segments in terms of turns and thereby predicting
approaching bus stops.In this methodology design it avoids dependence on
GPS functionality and instead relies on compass sensors, which are far more
Another method is Intelligent Transportation System for
Detection and Control of Congested Roads in Urban Centers1.This paper
proposes the uses Intelligent Transportation Systems technology. ITSs use
advances in technology in the areas of processing, sensing and communication to
monitor the traffic conditions in a particular region, manage and decrease
congestion, and reduce the number of accidents.A Vehicular Network is an
important component in an ITS.It contains network,vehicles are equipped with
processors, sensors and wireless communication interfaces so that they can communicate
with one another and with the elements in the network infrastructure(RSU – Road
Side Unit), thus creating an ad hoc network while vehicles move through roads
and prevent congestion and improve the efficiency of transportation systems.
Table1 Comparison with other technique
for urban bus
Turn detection using
in terms of
Time and Complexity
F ENGINEERING AND TECHNOLOGY
Department of computer science
system for bus passengers that has the ability to seamlessly interconnect bus
passengers with the real-world public bus infrastructure. The UBN relies on a
distributed IoT system comprising an embedded bus computing system, backend
computing infrastructure and a mobile smartphone app to detect the presence of
passengers on buses and provide continuous real-time navigation over the
complete course of a bus journey.One of the limitation of UBN is typical
passengers have few problems making micro-navigation decisions as they can rely
on their eye-sight, memory, prior knowledge and general reasoning abilities.
Due to substantial investment costs the system are only deployed in selected
cities and often lack information with traveler information systems. UBN is indeed
experienced by passengers as true navigation system and conceived differently
from existing mobile transport apps. All in all, UBN demonstrates the potential
of the IoT for delivering innovative urban transport experiences and enhances
the use of public transportation services.
1 Brennand, C. A. R. L., de Souza, A. M., Maia,
G., Boukerche,A., Ramos, H., Loureiro, A. A. F., and
V illas, L. A. (2015).An intelligent
transportation system for detection and control of congested roads
in urban centers.Pages 663–668.
2 Chenchik, D., Chen, J., Yan, S., and Nirjon,
S. (2017).Characterizing road segments using compass
sensors to predict approaching bus
3 Göka?ar, I. and Çetinel, Y.
(2017).Evaluation of bus dwelling patterns using bus gps data.pages 867–
4 Hu, X., Yang, L., and Xiong, W. (2015).A
novel wireless sensor network frame for urban
transportation.IEEE Internet of
Things Journal, 2(6):586–595.
5 Jodoin, J. P., Bilodeau, G. A., and Saunier,
N. (2016).Tracking all road users at multimodal urban
Transactions on Intelligent Transportation Systems,17(11):3241–3251.
6 Handte, M., Foell, S., Wagner, S., Kortuem,
G., and Marrón,P. J. (2016).An internet-of-things
enabled connected navigation system for
urban bus riders.IEEE Internet of Things Journal, 3(5):735–
7 S. Stradling, M. Carreno, T. Rye, and A.
Noble, Passenger perceptions and the ideal urban bus
journey experience, Transp. Pol., vol.
14, no. 4,pp. 283–292,(2007).
8 B. Gardner and C. Abraham, What drives car
use? A grounded theory analysis of commuters’ reasons
for driving, Transp. Res. F, Traffic
Psychol. Behav., vol. 10, no. 3, pp. 187–200,(2007).
9 T. D. Camacho, M. Foth, and A. Rakotonirainy,
Pervasive technology and public transport:
Opportunities beyond telematics, IEEE
Pervasive Comput., vol. 12, no. 1, pp. 18–25, Jan./Mar(2013).
J. Hare, L. Hartung, and S. Banerjee, Beyond deployments and
testbeds:Experiences with public
usage on vehicular WiFi hotspots, in Proc.
10th Int. Conf. Mobile Syst. Appl. Serv. (MobiSys),
Ambleside, U.K,pp. 393–406,(2012).