Automatic Train Control System using Wireless Sensor Networks

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Running trains using wireless sensors. For any communication, mail id - prakharbansal1@gmail.com

Running trains using wireless sensors. For any communication, mail id - prakharbansal1@gmail.com

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  • 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. Prakhar Bansal, MNNIT Allahabad 20 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 21 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 22 / 66 Automatic Train Control System
  • 23. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References Proposed Architecture Figure: Train Running Signalling using WSN Prakhar Bansal, MNNIT Allahabad 23 / 66 Automatic Train Control System
  • 24. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References Proposed Architecture Figure: Convergence and Divergence using WSN Prakhar Bansal, MNNIT Allahabad 24 / 66 Automatic Train Control System
  • 25. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References Proposed Architecture Figure: WSN based Interlocking Prakhar Bansal, MNNIT Allahabad 25 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 26 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 27 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 28 / 66 Automatic Train Control System
  • 29. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References After Algorithm 1 Figure: After Blockhead Configuration Prakhar Bansal, MNNIT Allahabad 29 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 30 / 66 Automatic Train Control System
  • 31. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References After Algorithm 2 Figure: After Clusterhead Configuration Prakhar Bansal, MNNIT Allahabad 31 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 32 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 33 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 34 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 35 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 37 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 38 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 39 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 39 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 40 / 66 Automatic Train Control System
  • 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] Prakhar Bansal, MNNIT Allahabad 41 / 66 Automatic Train Control System
  • 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). Prakhar Bansal, MNNIT Allahabad 42 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 43 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 44 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 45 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 46 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 46 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 47 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 48 / 66 Automatic Train Control System
  • 51. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References Simulation Experiences Initial Design I Figure: Initial Design with 1000 Nodes Prakhar Bansal, MNNIT Allahabad 49 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 50 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 51 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 52 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 53 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 54 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 55 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 56 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 57 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 58 / 66 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 Prakhar Bansal, MNNIT Allahabad 59 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 60 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 61 / 66 Automatic Train Control System
  • 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 Prakhar Bansal, MNNIT Allahabad 62 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 63 / 66 Automatic Train Control System
  • 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. Prakhar Bansal, MNNIT Allahabad 65 / 66 Automatic Train Control System
  • 68. Outline Motivation Present Signalling Field Study Thesis Contributions Simulation Conclusion References Thankyou Questions Please. Prakhar Bansal, MNNIT Allahabad 66 / 66 Automatic Train Control System