This document outlines an automatic train control system for railways using a wireless sensor network. It begins with an introduction and motivation for the project, describing the current railway signalling architecture and opportunities for improvement. The document then presents the author's field study and interactions with railway officials. It proposes a new WSN-based architecture and algorithms for train detection, clearance seeking, data aggregation and topology maintenance. It concludes with an overview of the simulation implementation in TinyOS and TOSSIM to test the proposed system and algorithms.
Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving within limited acceleration ranges. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead.
Advanced driver assistance systems are designed to increase car safety more generally road safety.
Basically Advanced driver assists(ADS) systems helps the driver in the driving process and enables safe, relaxed driving. It makes sense to get your new car with driver assist features if you find it at a reasonable price as it helps you drive easily and safely in everyday use.
Adaptive cruise control (ACC) provides assistance to the driver in the task of longitudinal control of their vehicle during motorway driving within limited acceleration ranges. The system controls the accelerator, engine powertrain and vehicle brakes to maintain a desired time-gap to the vehicle ahead.
Advanced driver assistance systems are designed to increase car safety more generally road safety.
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Automatic Train Collision and Accidence Avoidance systemPradeepRaj
This is an idea presentation, which can be implemented in near future to drastically reduce the rate of train accidents.
It is based on the concept of Piezoelectric sensor, Ultrasonic sensor and Pattern recognition.
A best and easy documentation about automatic braking system that may gives you a brief knowledge of Automatic Braking System related to Ultrasonic Sensor.
Embedded systems, especially in-vehicle embedded systems, are ubiquitously related to our everyday life. The development of embedded systems greatly facilitates the comfort of people’s life, changes our view of things, and has a significant impact on society
Sensors In Automobiles - Information is collected from various sources including Wikipedia,and others.The file above may be a edited or modified version of an already uploaded file on the internet such as on any other website or so.
Microstrip circular patch array antenna for electronic toll collectioneSAT Journals
Abstract Electronic toll collection will reduce the wastage of time at toll gates and collects the money in fast manner. At toll collection stations on the highway, the automatic toll collection will collect the money using one sensing antenna and the signal processing unit with the help of computer interfacing. The technology will reduce the man power usage, time and cost with customer friendly environment. The present paper deals with the design and analysis of electronic toll collection antenna operating at 5.8 GHz with moderate gain and bandwidth. An array of 6X6 elements patch antenna is used in this design, which increased the gain considerably for the desired operation. Keywords: Parallel Feeding, Electronic Toll Collection (ETC), Microstrip Patch Array.
Automatic Train Collision and Accidence Avoidance systemPradeepRaj
This is an idea presentation, which can be implemented in near future to drastically reduce the rate of train accidents.
It is based on the concept of Piezoelectric sensor, Ultrasonic sensor and Pattern recognition.
A best and easy documentation about automatic braking system that may gives you a brief knowledge of Automatic Braking System related to Ultrasonic Sensor.
Embedded systems, especially in-vehicle embedded systems, are ubiquitously related to our everyday life. The development of embedded systems greatly facilitates the comfort of people’s life, changes our view of things, and has a significant impact on society
Sensors In Automobiles - Information is collected from various sources including Wikipedia,and others.The file above may be a edited or modified version of an already uploaded file on the internet such as on any other website or so.
Microstrip circular patch array antenna for electronic toll collectioneSAT Journals
Abstract Electronic toll collection will reduce the wastage of time at toll gates and collects the money in fast manner. At toll collection stations on the highway, the automatic toll collection will collect the money using one sensing antenna and the signal processing unit with the help of computer interfacing. The technology will reduce the man power usage, time and cost with customer friendly environment. The present paper deals with the design and analysis of electronic toll collection antenna operating at 5.8 GHz with moderate gain and bandwidth. An array of 6X6 elements patch antenna is used in this design, which increased the gain considerably for the desired operation. Keywords: Parallel Feeding, Electronic Toll Collection (ETC), Microstrip Patch Array.
Microstrip circular patch array antenna for electronic toll collectioneSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Three phase induction motor Induction is one of the widest spread motor due to its
robustness, simple construction, no need for complex circuits for starting. With several
available speed control techniques, this paper presents a new Proportional-Integral (PI)
controller and Artificial Neural Network (ANNs) control system based on vector control
scheme. MATLAB/SIMULINK software may be used to create a 3phase induction engine
model. To achieve the effectiveness of the controller, the system is subjected to external
disturbance. Experimental results are presented and satisfied with the controller results.
Smart railway crossing embedded with automated platform bridgeeSAT Journals
Abstract The objective of this paper deals with automatic railway gate opening at a level crossing without human intervention. In the present work it is proposed to substitute fully automated railway gate opening feature and as well as automated platform bridge facility in the station which helps peoples to move from flat form to flat form. Now a day all over the world accidents are common because of lack of technology, human carelessness at right time. And these accidental barriers cannot be completely avoidable but some fruitful steps definitely reduced to some extent, in account of this the initiative steps is required to avoid many humans death at any place and time by introducing new technologies, this effort has been taken in this work by adopting automatic railway gate opening without gate keeper near level crossing and automated platform bridge. The above said system works on microcontroller based technique and rack and pinion mechanism which is employed to operate Platform Bridge. Keywords: Level crossing, Automated platform bridge
Help the Genetic Algorithm to Minimize the Urban Traffic on IntersectionsIJORCS
Control of traffic lights at the intersections of the main issues is the optimal traffic. Intersections to regulate traffic flow of vehicles and eliminate conflicting traffic flows are used. Modeling and simulation of traffic are widely used in industry. In fact, the modeling and simulation of an industrial system is studied before creating economically and when it is affordable. The aim of this article is a smart way to control traffic. The first stage of the project with the objective of collecting statistical data (cycle time of each of the intersection of the lights of vehicles is waiting for a red light) steps where the data collection found optimal amounts next it is. Introduced by genetic algorithm optimization of parameters is performed. GA begin with coding step as a binary variable (the range specified by the initial data set is obtained) will start with an initial population and then a new generation of genetic operators mutation and crossover and will Finally, the members of the optimal fitness values are selected as the solution set. The optimal output of Petri nets CPN TOOLS modeling and software have been implemented. The results indicate that the performance improvement project in intersections traffic control systems. It is known that other data collected and enforced intersections of evolutionary methods such as genetic algorithms to reduce the waiting time for traffic lights behind the red lights and to determine the appropriate cycle.
Adaptive notch filter under indirect and direct current controls for active p...journalBEEI
This study presents the implementation of adaptive notch filter (ANF) as reference signal extraction for shunt active power filter (APF) in indirect current control (ICC) and direct current control (DCC) modes for three phase system. The ANF functions to filter the signal that inputted to it by producing a fundamental signal and harmonics signal. The advantage of applying the ANF algorithm is based on its simple design that giving the ANF advantages to be utilize in microcontroller. The performance of the ANF is validated though MATLAB simulation in ICC dan DCC configurations. Based on the simulation results, the ANF is capable to work efficiently for both ICC and DCC modes, but in term of efficiency, the ICC mode is clearly showing a better harmonics mitigation result. Base on the result also it shown that the ANF is capable of mitigate the harmonics below the standard required by the IEEE 519-92. The application of ANF is useful to be applied due to its simple design and filtering method.
Ride comfortability of vehicle is a big challenge for the automotive industries and design engineers. The suspension system is the major source of providing comfortability by absorbing vertical vibrations. This paper presents modeling of the non-linear semi-active suspension system equipped with Magneto Rheological damper. Simulation of the designed model is performed in Simulink. A comparative analysis of the Simulink response shows the difference between linear and non-linear model. It has also shown that fuzzy logic controller has improved the performance of the system.
Application and evaluation of the neural network in gearboxTELKOMNIKA JOURNAL
We developed old designed of a Back-Propagation neural network (BPNN), which it was designed by other researchers, and we made modification in their structure. The 1st velocity ratio was discriminated by lowest speed, and highest twist. The 6th velocity ratio was discriminated by highest speed, and lowest twist. The aim of this paper is to design neural structure get best performance to control an electrical automotive transportation six-speed gearbox of the vehicle. We focus on the evaluation of the BPNN to select the suitable number of layers and neurons. Experimentally, the structure of the proposed BPNN are constructed from four layers: eight input nodes in the first layer that received data in binary number, 45 neurons in 1st hidden-layer, 25 neurons in 2nd hidden-layer, and 6 neurons in the fourth layer. The MSE and number of Epochs are the main factors used for the evaluation of the proposed structure, and compared with the other structures which was designed by other researchers. Experimentally, we discovered that the best value of Epoch and MSE was chosen when the BPNN consisted of two hidden-layers, 45, and 25 neurons in the 1st and 2nd hidden-layer respectively. The implementation was applied using MATLAB software.
Direct Torque Control (DTC) of Induction Motor drive has quick torque response without complex orientation transformation and inner loop current control. DTC has some drawbacks, such as the torque and flux ripple. The control scheme performance relies on the accurate selection of the switching voltage vector. This proposed simple structured neural network based new identification method for flux position estimation, sector selection and stator voltage vector selection for induction motors using direct torque control (DTC) method. The ANN based speed controller has been introduced to achieve good dynamic performance of induction motor drive. The Levenberg-Marquardt back-propagation technique has been used to train the neural network. Proposed simple structured network facilitates a short training and processing times. The stator flux is estimated by using the modified integration with amplitude limiter algorithms to overcome drawbacks of pure integrator. The conventional flux position estimator, sector selector and stator voltage vector selector based modified direct torque control (MDTC) scheme compared with the proposed scheme and the results are validated through both by simulation and experimentation.
LIGHTWEIGHT MOBILE WEB SERVICE PROVISIONING FOR THE INTERNET OF THINGS MEDIATIONijujournal
Emerging sensor-embedded smartphones motivated the mobile Internet of Things research. With the
integrated embedded hardware and software sensor components, and mobile network technologies,
smartphones are capable of providing various environmental context information via embedded mobile
device-hosted Web services (MWS). MWS enhances the capability of various mobile sensing applications
such as mobile crowdsensing, real time mobile health monitoring, mobile social network in proximity and
so on. Although recent smartphones are quite capable in terms of mobile data transmission speed and
computation power, the frequent usage of high performance multi-core mobile CPU and the high speed
3G/4G mobile Internet data transmission will quickly drain the battery power of the mobile device.
Although numerous previous researchers have tried to overcome the resource intensive issues in mobile
embedded service provisioning domain, most of the efforts were constrained because of the underlying
resource intensive technologies. This paper presents a lightweight mobile Web service provisioning
framework for mobile sensing which utilises the protocols that were designed for constrained Internet of
Things environment. The prototype experimental results show that the proposed framework can provide
higher throughput and less resource consumption than the traditional mobile Web service frameworks.
SPEED AND TORQUE CONTROL OF AN INDUCTION MOTOR WITH ANN BASED DTCijics
Due to advantages such as fast dynamic response, simple and robust control structure, direct torque
control (DTC) is commonly used method in high performance control method for induction motors. Despite
mentioned advantages, there are some chronically disadvantages with this method like high torque and
current ripples, variable switching behaviour and control problems at low speed rates. On the other hand,
artificial neural network (ANN) based control algorithms are getting increasingly popular in recent years
due to their positive contribution to the system performance. The purpose of this paper is investigating of
the effects of ANN integrated DTC method on induction motor performance by numerical simulations. For
this purpose, two different ANN models have been designed, trained and implemented for the same DTC
model. The first ANN model was designed to select optimum inverter and the second model was designed to
use in the determination of the flux vector position. Matlab/Simulink model of the proposed ANN based
DTC method was created in order to compare with the conventional DTC and the proposed DTC methods.
The simulation studies proved that the induction motor torque ripples have been reduced remarkably with
the proposed method and this approach can be a good alternative to the conventional DTC method for
induction motor control.
An IoT based Dynamic Traffic Signal ControlGauthamSK4
Used Kerner three-phase traffic theory to establishing an Intelligent Traffic System that will provide automatic management of traffic lights based on the concept of the Internet of Things which will resolve the traffic jam issues which will in turn reduce CO2 emissions and also the mobility metrics like the travel time.
April 2020: Top Read Articles in VLSI design & Communication SystemsVLSICS Design
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Automatic Train Control System using Wireless Sensor Networks
1. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Automatic Train Control System for Railways
using Wireless Sensor Network
Prakhar Bansal
2011CS29
under the guidance of
Prof. M.M. Gore
Computer Science and Engineering Department
Motilal Nehru National Institute of Technology Allahabad,
Allahabad, India
June 11, 2013
Prakhar Bansal, MNNIT Allahabad 1 / 66
Automatic Train Control System
2. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
Prakhar Bansal, MNNIT Allahabad 2 / 66
Automatic Train Control System
3. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
Prakhar Bansal, MNNIT Allahabad 3 / 66
Automatic Train Control System
4. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Motivation
Why Railways?
Figure: i.) Railways as a Transportation ii.) Frequency of Rail Accidents
iii.) Need of Sustainable Transport Solution
Prakhar Bansal, MNNIT Allahabad 4 / 66
Automatic Train Control System
5. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Motivation
Railways as a Transport
Railways as a Passenger Solution
44446 million passengers travel globally/year via railways [1].
6.8% people travel via rail all over the world [1].
24 million people/day travel via rail in India [2].
Japan, China and Russia has high passenger modal split of
29%, 31.7% and 41.1% respectively [3].
Railways as a Carriage Solution
5439 mtk goods is carried via rail globally in 2011 [1].
IR carries 2.8 million tons of freight/day [4].
USA and Russia has rail freight modal share of 88.8% and
67.9% respectively [5].
Prakhar Bansal, MNNIT Allahabad 5 / 66
Automatic Train Control System
6. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Motivation
Accidents Rate
Old technology and manual signalling in most countries.
More than 1000 people die per year globally [6].
715 people die and 1118 injured in last 3 years in 49 accidents
in India [2].
Mostly accidents happen due to manual errors in signalling,
lack of visibility, communication faults and derailments [5].
Trains usually run out of schedule and even get canceled in
winter season due to low visibility.
Prakhar Bansal, MNNIT Allahabad 6 / 66
Automatic Train Control System
7. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Motivation
Need for Sustainable Transport
Figure: (a) CO2 Emissions [7] Figure: (b) Energy Consumption [7]
Prakhar Bansal, MNNIT Allahabad 7 / 66
Automatic Train Control System
8. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Motivation
Need for Sustainable Transport
Table: CO2 Emissions [7]
Rail 48.8 gram/passenger/km
Roads 418 gram/passenger/km
Navigation 200 gram/passenger/km
Aviation 316 gram/passenger/km
Table: CO2 Emissions in India in the period 1998-2009 [8]
Rail 8 million tons
Roads 128 million tons
Navigation 18 million tons
Aviation 4 million tons
Prakhar Bansal, MNNIT Allahabad 8 / 66
Automatic Train Control System
9. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
Prakhar Bansal, MNNIT Allahabad 9 / 66
Automatic Train Control System
10. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Present Railway Signalling Architecture
Figure: General Signalling Boards
Prakhar Bansal, MNNIT Allahabad 10 / 66
Automatic Train Control System
11. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Present Railway Signalling Architecture
Figure: Color Light Signals
Prakhar Bansal, MNNIT Allahabad 11 / 66
Automatic Train Control System
12. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Present Railway Signalling Architecture
Figure: Semaphore Signals
Prakhar Bansal, MNNIT Allahabad 12 / 66
Automatic Train Control System
13. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Present Railway Signalling Architecture
Figure: Convergence and Divergence Signals
Prakhar Bansal, MNNIT Allahabad 13 / 66
Automatic Train Control System
14. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Present Railway Signalling Architecture
Figure: Shunting and Repeater Signals
Prakhar Bansal, MNNIT Allahabad 14 / 66
Automatic Train Control System
15. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Successfully Deployed WSN Projects
Smart-Grid Project [9]: entire process from generation,
transmission, distribution of electricity to integration of
renewable and alternative energy sources, is handled by
wireless sensors.
Microsoft SensorMap [10]:
100s of mini weather stations deployed in schools throughout
Singapore.
sensor grid, to automatically collect and aggregate the weather
data in real time.
studies correlation between the weather patterns and dengue
fever.
CodeBlue [11]: wireless sensors for medical care.
Ultra-wideband sensing and communication for biomedical
applications [12].
Prakhar Bansal, MNNIT Allahabad 15 / 66
Automatic Train Control System
16. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
Prakhar Bansal, MNNIT Allahabad 16 / 66
Automatic Train Control System
17. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Field Study
Interaction with Senior Section Engineer, North Central Railways
Figure: Ghaziabad Train Control
Room c Indian Railways [13]
Figure: Typical Train Control Room
c Indian Railways [13]
Prakhar Bansal, MNNIT Allahabad 17 / 66
Automatic Train Control System
18. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Study Findings
Lots of mechanical equipments used [14].
Completely depends on manual expertise.
As traffic increasing, needs good computerized managing
solutions.
Route relay interlocking installed only on busy stations.
Prakhar Bansal, MNNIT Allahabad 18 / 66
Automatic Train Control System
19. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
WSN Suitability to Railways
Huge scope of wsn in railways [15].
Think about station master itself getting incoming train
readings via sensors.
No need for manual signalling.
Train itself asks for clearance to next block head, no need to
stop and wait.
Accurate location information without GPS.
Prakhar Bansal, MNNIT Allahabad 19 / 66
Automatic Train Control System
20. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Use of Self-recharging Batteries from Vibrations
Piezoelectric vibrational energy harvester (PZeh) are used.
Generates 40mW on an average with a peak operation of
0.3W, when shaken gently.
Generates 280mW with a peak operation of 2.0W, when
shaken vigorously.
Micaz mote processor consumes 8mA in Active mode and
<15µ A Sleep mode.
Micaz mote radio consumes 19.7mA in Receiving mode,
17.4mA TX, 0dBm, 20µA Idle mode, voltage regular ON and
1µA Sleep mode, voltage regulator OFF.
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21. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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22. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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23. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Proposed Architecture
Figure: Train Running Signalling using WSN
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24. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Proposed Architecture
Figure: Convergence and Divergence using WSN
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25. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Proposed Architecture
Figure: WSN based Interlocking
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26. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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27. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Train Running Algorithms
Algorithms
Algorithm 1: Configuration Phase - Learning the BHs
Algorithm 2: Configuration Phase - Learning the CHs
Algorithm 3: Train Event Detection: Seeking Clearance by
BHs
Algorithm 4: Data Aggregation and Forwarding: Data to CHs
Algorithm 5: Topology Updation and Maintenance
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28. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Algorithm 1
Algorithm 1 Configuration Phase: Learning the BHs
BH/Station broadcasts a ‘configuration message’CM with a
BHdistance = 1
Ru is the set of nodes that receive the CM message
for each u ∈ Ru do
i=0
if BHdistanceu > BHdistanceCM and
firstsendingu[BhIDCM ]==true and isBH==false then
nextbhu[i] ← BhIDCM
nexthopu[i] ← NIDCM
BHdistanceu ← BHdistanceCM + 1
NIDCM ← TOS NODE ID
BHdistanceCM ← BHdistanceu
node u broadcast the modified CM msg
firstsendingu[BhIDCM ] ← false
i++
else
node u discards the received CM message
end if
end for
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29. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
After Algorithm 1
Figure: After Blockhead Configuration
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30. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Algorithm 2
Algorithm 2 Configuration Phase: Learning the CHs
Clusterhead broadcasts a Clusterhead Declaration Message
(CDM) with a TTL value
Ru is the set of nodes that receive the CDM message
for each u ∈ Ru do
if TTL = 0 and u ∈ BH then
if CDM− > ID /∈ CHQueueu then
add(CHQueueCH, CDM− > ID)
TTL ← TTL − 1
node u broadcasts modified CDM message
end if
else
node u discards the received CDM message
end if
end for
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31. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
After Algorithm 2
Figure: After Clusterhead Configuration
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32. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Algorithm 3
Algorithm 3 Train Event Detection and Seeking for Clearance
Ru is the set of nodes that detect train
for each u ∈ Ru do
if TrainDetectedu == true and DoubleLane==true then
if flagu == 0 then
// critical section
send clearance signal
flagu = 1
end if
else
send wait signal
end if
if TrainDetectedu == true and DoubleLane==false and
stationu == true then
if flagu == 0 and flagNextStationu == 0 then
// critical section
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33. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Algorithm 3
Algorithm 3 Train Event Detection and Seeking for Clearance
(cont.)
send clearance signal
flagu = 1
flagNextStationu = 1
end if
else
send wait signal
end if
if TrainLeavesu == true and DoubleLane==true then
send clearance signal to neighboring BH
end if
if TrainLeavesu == true and DoubleLane==false and
stationu == true then
send clearance signal to neighboring station
end if
end for
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34. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Algorithm 4
Algorithm 4 Data Aggregation and Forwarding
Ru is the set of BH/Station
for each u ∈ Ru do
Each BH/Station periodically sends the list of train to all CHs
in the queue
Packet.msg ← TrainInfou
add(Packet.ID[ ], TOS NODE ID)
//The BH/Station, when receives the list from other
BHs/Stations, it aggregates the data and then forwards it
if Packet Received then
buffer=buffer∪Packet
Packet ← buffer
forwards Packet
end if
end for
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35. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Algorithm 5
Algorithm 5 Topology Updation and Maintenance
if train list not received by CH or partial list is received then
restart algorithm 1 and 2
end if
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36. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
Prakhar Bansal, MNNIT Allahabad 36 / 66
Automatic Train Control System
37. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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38. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
TinyOS, nesC and TOSSIM
TinyOS
TinyOS
Free, open-source, BSD-licensed OS designed for low-power
embedded distributed wireless sensor devices [16].
Developed by University of California, Berkeley, Intel Research
and Crossbow Technology.
Designed to support the concurrency intensive operations
required by networked sensors with minimal hardware
requirements.
Written in nesC programming language.
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39. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
TinyOS, nesC and TOSSIM
nesC and TOSSIM
nesC
Network embedded systems C, C optimized to support
components and concurrency [17].
Component based, event driven programming language used
to build application for TinyOS platform.
Components are wired together to run applications on
TinyOS.
Programs = software components (connected statically via
interfaces).
TOSSIM
Simulates entire TinyOS applications [18].
Replaces components with simulation implementations.
2 interfaces: c++ and python.
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40. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
TinyOS, nesC and TOSSIM
nesC and TOSSIM
nesC
Network embedded systems C, C optimized to support
components and concurrency [17].
Component based, event driven programming language used
to build application for TinyOS platform.
Components are wired together to run applications on
TinyOS.
Programs = software components (connected statically via
interfaces).
TOSSIM
Simulates entire TinyOS applications [18].
Replaces components with simulation implementations.
2 interfaces: c++ and python.
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41. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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42. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Sensor Motes and Sensor Boards
MICAz Mote
Figure: MICAz Sensor Mote c Crossbow Technology, USA [19]
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43. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Sensor Motes and Sensor Boards
MICAz Mote
2.4 GHz mote for enabling low-power wireless sensor networks.
IEEE 802.15.4 compliant Radio frequency transceiver.
Radio, resistant to RF interference and provides inherent data
security.
Atmel128L, low power microcontroller.
51-pin expansion connector.
High speed (250 Kbps), hardware security (AES-128).
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44. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Sensor Motes and Sensor Boards
Sensor Boards
MTS400CA
Acceleration: dual-axis acceleration sensor.
Atmospheric pressure: barometric pressure sensor.
Light: ambient light sensor.
Humidity and temperature: relative humidity and temperature
sensor.
MDA100CB
Light: light sensor and photocell.
92 unconnected soldering points.
51-pin connector.
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45. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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46. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Routing Protocols
Collection Tree Protocol
Collecting data from motes.
One or more collection trees is built, each of which is rooted
towards the specified destination.
When a node has data which needs to be collected, it sends
the data up the tree, and it forwards collection data that
other nodes send to it after aggregating, or suppressing
redundant transmissions.
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47. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Routing Protocols
Dissemination
It is used to maintain consistency across the network.
The dissemination service tells nodes when the value changes,
and exchanges packets so it will reach eventual consistency
across the network.
Blip
BLIP, the Berkeley Low-power IP stack, is an implementation
in TinyOS of a number of IP-based protocols.
Internet of things.
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48. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Routing Protocols
Dissemination
It is used to maintain consistency across the network.
The dissemination service tells nodes when the value changes,
and exchanges packets so it will reach eventual consistency
across the network.
Blip
BLIP, the Berkeley Low-power IP stack, is an implementation
in TinyOS of a number of IP-based protocols.
Internet of things.
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49. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Routing Protocols
Tymo
TYMO is the implementation on TinyOS of the DYMO
[Dynamic MANET On-demand] protocol, a point-to-point
routing protocol for MANET.
TYMO, packet format is changed and implemented on top of
the Active Message stack of TinyOS.
Reactive protocol, DYMO does not explicitly store the
network topology.
Nodes compute a unicast route towards the desired
destination only when needed using RREQ and RREP packets.
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50. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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51. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences
Initial Design I
Figure: Initial Design with 1000 Nodes
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52. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences
Initial Design II
Figure: Design with Clearance Points along Stations but not along
Junctions with 100 Nodes
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53. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences
Design with BHs but not Intermediate Nodes
Figure: Introduction to Block System with 100 Nodes
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54. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences
Design with BHs with Intermediate Nodes
Figure: Revised Block System Architecture with 115 Nodes
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55. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences
Final Architecture: BHs + CHs + Intermediate Motes
Figure: Present Architecture with 125 Nodes
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56. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences
Topology Framework with respect to Allahabad Junction
Figure: Topology Framework with respect to Allahabad Junction
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57. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences
Topology Framework with respect to Allahabad Junction
Figure: Topology Framework with respect to Allahabad Junction
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58. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences and Results
Results with Variable Number of Nodes
Figure: (a) Energy Consumption
with Variable Number of Nodes
Figure: (b) Success Rate with
Variable Number of Nodes
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59. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences and Results
Results with Variable Frequency of Trains across Allahabad Junction
Figure: (a) Energy Consumption
with Variable Frequency of Trains
across Allahabad Junction
Figure: (b) Success Rate with
Variable Frequency of Trains across
Allahabad Junction
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60. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Simulation Experiences and Results
Discussions
In our work we used the energy model where the radio
dissipates energy E = 50 nJ/bit to run the transmitter or
receiver circuitry and amp = 100 pJ/bit/m2 for the transmit
amplifier to achieve an acceptable SNR [20].
Simulation maximum duration is 10000 seconds and it runs 8
rounds/set of nodes.
Topology is generated randomly in each run when doing
simulation for variable number of nodes and it is fixed for
simulation across Allahabad junction.
The success rate is currently decreasing as the number of
packets increase in the network. This is due to collisions of
messages. This needs to be improved.
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Automatic Train Control System
61. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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62. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Conclusion
This could be a revolution in railway technology.
Trains can run efficiently and accurately as any error can be
easily detected.
Trains can run in low visibility as sensors would take care of
this.
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63. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Future Work
Integration with Internet of things evolution using Blip
effectively.
Security as false messages can be spread by attackers;
authenticity and confidentiality could be introduced using
cryptographic solutions.
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64. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Table of Contents
1 Motivation
2 Introduction to Present Railway Signalling Architecture
3 Field Study
4 Thesis Contributions
Proposed Architecture
Algorithms
5 Simulation Implementation
TinyOS, nesC and TOSSIM
Sensor Motes and Sensor Boards
Routing Protocols
Simulation Experiences and Results
6 Conclusion and Future Work
7 References
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65. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
References I
World Bank Data. http://data.worldbank.org/indicator/IS.RRS.TOTL.KM.
[Online; last accessed June 10, 2013].
Anil Kakodkar, E. Sreedharan, N.Vedachalam, “Report of High Level Safety Review Committee,” Ministry
of Railways, Government of India, February, 2012.
Hiroumi Soejima, “Railway Technology in Japan Challenges and Strategies,” Japan Railway and Transport
Review, September, 2003.
Pawan Bansal, “Speech by Railway Minister,” Ministry of Railways, Government of India, February, 2012.
Sam Pitroda, Deepak Parekh and M.S. Verma, “Report of the Expert Group for Modernizaion of Indian
Railways,” Ministry of Railways, Government of India, February 2012.
Amitabh Agarwal, “Human Interface in Railway Safety? A New Dimension,” Ministry of Railways,
Government of India, 2007.
Jean-Pierre Loubinoux, “Keeping Climate Change Solutions on Track The Role of Rail,” International Union
of Railways, March 2012.
Tan Yigitcanlar, Lawrence Fabian and Eddo Coiacetto, “Challenges to Urban Transport Sustainability and
Smart Transport in a Tourist City: The Gold Coast, Australia,” The Open Transportation Journal, 2008.
Murtala Aminu Bamanga, “Wireless Sensor Network Applications in Smart Grid,” University of sussex, 2012.
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66. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
References II
Suman Nath, Jie Liu, and Feng Zhao, “SensorMap for Wide-Area Sensor Webs.”
http://atom.research.microsoft.com/sensewebv3/sensormap/.
[Online; last accessed on June 10, 2013].
Matt Welsh, “CodeBlue: A Wireless Sensor Network for Medical Care and Disaster Response,” Harvard
University, 2005.
“Ultra-wideband Sensing and Communication for Biomedical Applications.”
http://www.sussex.ac.uk/crg/projects/wsn/uwbsens/, University of Sussex.
[Online; last accessed June 10, 2013].
Karan Desai, “Akamai Technologies, Inc..” http://www.quora.com/India/
How-does-the-inside-of-control-room-of-Indian-railways-look-like-How-do-the-guys-in-the-control-r
[Online; last accessed on June 10, 2013].
Mr. Alok Sehgal. Senior section engineer, North Central Railways, Allahabad railway station.
Yamato Fukuta, “Possibility of Sensor Network Applying for Railway Signal System,” IEEE conference, 2008.
P. Levis and D. Gay, TinyOS Programming.
New York, NY, USA: Cambridge University Press, 1st ed., 2009.
David Gay, Philip Levis, Matt Welsh and David Culler, “The nesC Language: A Holistic Approach to
Networked Embedded Systems,” 2002.
Prakhar Bansal, MNNIT Allahabad 64 / 66
Automatic Train Control System
67. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
References III
P. Levis, N. Lee, M. Welsh, and D. Culler, “Tossim: accurate and scalable simulation of entire tinyos
applications,” in Proceedings of the 1st international conference on Embedded networked sensor systems,
SenSys ’03, (New York, NY, USA), pp. 126–137, ACM, 2003.
Crossbow Technology, “Micaz Specification.”
www.openautomation.net/uploadsproductos/micaz_datasheet.pdf.
[Online; last accessed June 10, 2013].
Leandro Aparecido Villas, Azzedine Boukerche and Heitor Soares Ramos,, “DRINA: A Lightweight and
Reliable Routing Approach for In-Network Aggregation in Wireless Sensor Networks,” vol. 62, IEEE
Transactions on Computers, April 2013.
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68. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References
Thankyou
Questions Please.
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