Preface |
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xi | |
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Chapter 1 Public Warning Applications: Requirements and Examples |
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1 | (18) |
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1 | (1) |
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1.2 Emergency management communications |
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2 | (3) |
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1.3 Public warning systems |
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5 | (3) |
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1.4 Public warning applications |
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8 | (3) |
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1.5 Exemplary case: the Alert4All approach |
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11 | (5) |
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1.5.1 HbbTV-enabled receivers |
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12 | (2) |
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14 | (2) |
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16 | (1) |
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17 | (2) |
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Chapter 2 An Innovative and Economic Management of Earthquakes: Early Warnings and Situational Awareness in Real Time |
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19 | (20) |
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19 | (3) |
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2.2 Motivation and previous works |
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22 | (1) |
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23 | (11) |
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2.3.1 Smartphone application and acceleration processing |
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27 | (2) |
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2.3.2 Server intermediate application |
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29 | (4) |
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33 | (1) |
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34 | (1) |
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35 | (1) |
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36 | (3) |
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Chapter 3 Community Early Warning Systems |
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39 | (28) |
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3.1 Core early warning system components |
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40 | (6) |
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40 | (2) |
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42 | (1) |
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3.1.3 Response capability |
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43 | (1) |
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3.1.4 Warning communication |
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44 | (2) |
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3.2 Time scenarios for EWS |
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46 | (3) |
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46 | (1) |
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3.2.2 Management of the time in the distributed real-time systems |
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47 | (2) |
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3.3 Core early warning system components using smartphones |
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49 | (2) |
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3.3.1 Technology progress |
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49 | (1) |
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3.3.2 Efficiency to warn the population |
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50 | (1) |
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50 | (1) |
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3.4 A smart city using smartphones into CEWS |
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51 | (11) |
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52 | (3) |
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55 | (3) |
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3.4.3 Roads and transportation |
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58 | (4) |
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62 | (1) |
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63 | (4) |
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Chapter 4 Generating Crisis Maps for Large-scale Disasters: Issues and Challenges |
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67 | (32) |
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4.1 Crisis mapping: "global" versus "local" |
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68 | (4) |
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4.1.1 Why crisis mapping? |
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68 | (1) |
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4.1.2 Crisis mapping: working principle |
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69 | (3) |
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4.2 Post-disaster communication revisited |
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72 | (7) |
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4.2.1 Post-disaster communication: state-of-the-art |
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72 | (3) |
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4.2.2 Post-disaster communication: possible alternatives |
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75 | (3) |
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4.2.3 Large-scale DTN systems for challenged scenarios |
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78 | (1) |
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4.3 Proposed solution in a nutshell |
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79 | (10) |
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4.3.1 Multi-tier hybrid architecture for post-disaster communication |
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79 | (4) |
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4.3.2 Implementation & testbed |
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83 | (1) |
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84 | (2) |
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4.3.4 Working principle of the proposed system |
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86 | (3) |
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4.4 Localized crisis mapping |
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89 | (4) |
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4.4.1 A system for offline crisis mapping |
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89 | (4) |
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93 | (2) |
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95 | (4) |
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Chapter 5 Context-Aware Public Safety in a Pervasive Environment |
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99 | (14) |
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Shivsubramani Krishnamoorthy |
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Prabaharan Poornachandran |
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Sujadevi Vijaya Gangadharan |
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100 | (1) |
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101 | (3) |
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103 | (1) |
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5.3 Context-aware middleware |
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104 | (1) |
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5.4 Practical experience -- implementation of AmritaMitra personal safety framework |
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105 | (5) |
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5.4.1 Sensing and alerting |
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105 | (2) |
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5.4.2 Cloud services and contextual analysis |
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107 | (1) |
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5.4.3 Social media as an emergency communication system |
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108 | (1) |
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5.4.4 Indoor and outdoor location identification |
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109 | (1) |
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5.4.5 Real-time user and context tracking |
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109 | (1) |
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5.5 Conclusion and future directions |
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110 | (1) |
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111 | (2) |
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Chapter 6 Supporting New Application and Services over LTE Public Safety Networks |
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113 | (20) |
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Cesar Agusto Garcia-Perez |
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114 | (1) |
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6.2 Motivation and background information |
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115 | (2) |
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115 | (1) |
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116 | (1) |
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6.3 Services for public safety networks |
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117 | (5) |
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6.3.1 Common challenges for current technologies in emergencies |
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118 | (1) |
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6.3.2 Specialized scenarios in public emergencies |
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119 | (3) |
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6.4 Wearable devices in public safety |
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122 | (8) |
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6.4.1 The BlueEye use case |
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122 | (1) |
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6.4.2 BlueEye for first responders |
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123 | (1) |
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6.4.3 VELOX API for public safety applications |
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124 | (6) |
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6.5 Conclusions and future work |
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130 | (1) |
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131 | (1) |
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131 | (2) |
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Chapter 7 Aerial Platforms for Public Safety Networks and Performance Optimization |
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133 | (22) |
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Sathyanarayanan Chandrasekharan |
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Sithamparanathan Kandeepan |
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7.1 Aerial supported public safety networks |
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134 | (3) |
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7.2 Air-to-ground radio channel |
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137 | (10) |
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7.2.1 The nature of the air-to-ground radio channel |
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138 | (1) |
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7.2.2 ABSOLUTE radio propagation model |
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139 | (6) |
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7.2.3 ABSOLUTE model implementation |
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145 | (2) |
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7.3 Optimizing the altitude of aerial platforms |
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147 | (5) |
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7.3.1 Modeling the probability of line-of-sight |
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148 | (1) |
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7.3.2 Modeling and optimizing system performance |
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149 | (3) |
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152 | (3) |
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Chapter 8 Topology Control for Drone Networks |
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155 | (30) |
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155 | (3) |
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158 | (1) |
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159 | (1) |
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8.4 Examples of drone applications |
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160 | (6) |
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166 | (1) |
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167 | (4) |
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8.7 Topology control requirements for network reliability |
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171 | (1) |
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8.8 Mission-based topology description |
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172 | (1) |
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8.9 Bases of the proposed method |
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173 | (2) |
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175 | (4) |
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179 | (2) |
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181 | (4) |
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Chapter 9 Safe and Secure Support for Public Safety Networks |
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185 | (26) |
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186 | (1) |
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187 | (1) |
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187 | (1) |
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188 | (1) |
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188 | (1) |
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9.4 Our approach: SysML-Sec |
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189 | (10) |
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189 | (1) |
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190 | (2) |
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9.4.3 Hardware/software partitioning |
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192 | (3) |
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9.4.4 Software/system design |
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195 | (1) |
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196 | (1) |
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196 | (1) |
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196 | (1) |
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197 | (1) |
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198 | (1) |
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199 | (4) |
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9.5.1 Mission description |
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201 | (1) |
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9.5.2 Integration of mission planning and autonomous vehicles |
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202 | (1) |
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203 | (4) |
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9.6.1 Embedded system design |
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203 | (2) |
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205 | (1) |
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206 | (1) |
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9.7 Conclusion and perspectives |
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207 | (1) |
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208 | (1) |
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208 | (3) |
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Chapter 10 Disaster Resilient Telematics based on Device-to-Device Communication |
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211 | (20) |
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212 | (2) |
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10.2 Public safety ad-hoc networking |
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214 | (2) |
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10.3 Beaconing-based proximate communication |
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216 | (2) |
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10.4 Beaconing-based networking |
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218 | (8) |
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10.4.1 Intelligent alert messaging |
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219 | (2) |
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10.4.2 Device localization |
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221 | (2) |
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10.4.3 Situation awareness |
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223 | (2) |
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10.4.4 Evacuation navigation |
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225 | (1) |
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226 | (1) |
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227 | (4) |
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Chapter 11 ICN/DTN for Public Safety in Mobile Networks |
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231 | (18) |
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231 | (2) |
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233 | (4) |
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237 | (4) |
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11.4 Example implementation |
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241 | (5) |
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241 | (2) |
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11.4.2 OVS virtual switch |
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243 | (1) |
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11.4.3 PS bundle at the network edge |
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244 | (2) |
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246 | (1) |
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246 | (3) |
List of Authors |
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249 | (4) |
Index |
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253 | |