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E-raamat: Microsensing Networks for Sustainable Cities

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This book explores the microsensing technologies and systems now available to monitor the quality of air and water within the urban environment and examines their role in the creation of sustainable cities against the background of the challenges posed by rapid urbanization. The opening section addresses the theoretical and conceptual background of microsensing networks. The coverage includes detailed description of microsensors, supported by design-specific equations, and clear explanation of the ways in which devices that harvest energy from ambient sources can detect and quantify pollution. The practical application of such systems in addressing environmental impacts within cities and in sustainable urban planning is then discussed with the aid of case studies in developing countries. The book will be of interest to all who wish to understand the benefits of microsensing networks in promoting sustainable cities through better delivery of information on health hazards and improv

ed provision of data to environmental agencies and regulatory bodies in order to assist in monitoring, decision-making, and regulatory enforcement.

Microsensing Networks for SustainableCities: Pollution as a Key Driving Factor.- PopulationGrowth in Developing Countries and Smart City Fundamentals. TheInternet-of-Things and Wireless Sensor Networks.- Modelling of Air and Water Pollution Sources.- Harvesting Energy from Ambient Sources: Wind Energy,Hydropower, Radiation and Mechanical Deformation.- The Sub-Systems of an Energy Harvesting Device: Focus on RFIDFundamentals.- Geographic Information Systems and Remote Sensing.- Ubiquitous Computing: Distributing Mobile Computing to Builda Global Network of Things.- Designing andPlanning for Sustainable Urbanism with Focus on Developing Countries.- Toolsand Facilitators towards Successful Planning for Sustainable Cities.- CaseStudies: Developing Countries Committed to an Ecologically Aware Future.
1 Microsensing Networks for Sustainable Cities: Pollution as a Key Driving Factor
1(28)
1.1 Introduction
1(1)
1.2 Urban Megacities
2(1)
1.3 Smart Cities
3(2)
1.4 Air Pollutants
5(2)
1.5 Air Pollution Sources
7(2)
1.6 Water Pollutants
9(1)
1.7 Water Pollution Sources
10(1)
1.8 Air Pollution Monitoring
11(2)
1.9 Water Pollution Monitoring
13(1)
1.10 Air Quality Sensors
14(1)
1.11 Water Quality Sensors
15(1)
1.12 The Internet-of-Things
16(2)
1.13 Wireless Sensing Networks
18(2)
1.14 Energy-Harvesting
20(2)
1.15 Geographic Information Systems and Remote Sensing
22(1)
1.16 Ubiquitous Computing
23(1)
1.17 Software Resources
24(1)
1.18 Conclusion
25(4)
References
25(4)
2 Population Growth in Developing Countries and Smart City Fundamentals. The Internet-of-Things and Wireless Sensor Networks
29(34)
2.1 Introduction
29(1)
2.2 Population Growth in Cities
29(1)
2.3 Carrying Capacity
30(2)
2.4 Variable Carrying Capacity
32(1)
2.5 Developing Country Growth Statistics
33(1)
2.6 Developed Country Growth Statistics
34(1)
2.7 Smart Cities
35(1)
2.8 Smart City Investments
36(2)
2.9 Smart City Initiatives
38(1)
2.10 Applications and Typical Environments
38(4)
2.11 Internet-of-Things
42(1)
2.12 Internet Access in Developing and Developed Nations
43(1)
2.13 Addressable Networked Devices
43(1)
2.14 IoT Market Share
44(2)
2.15 IoT and Smart City Word Usage
46(1)
2.16 Industrial IoT
47(2)
2.17 SCADA
49(1)
2.18 Wireless Sensor Networks
50(4)
2.19 Layered WSN Nodes
54(1)
2.20 WSN Topologies
54(2)
2.21 WSN Modelling
56(1)
2.22 WSN Reliability
57(4)
2.23 Conclusion
61(2)
References
61(2)
3 Modelling of Air and Water Pollution Sources
63(38)
3.1 Introduction
63(1)
3.2 Indoor Air Pollution
63(5)
3.3 Outdoor Air Pollution
68(1)
3.4 Ambient Air Pollution Modelling
69(2)
3.5 Pollutant Concentration Conversion
71(1)
3.6 Concentration in Altitude Variations
72(2)
3.7 Unsaturated Adiabatic Lapse Rate
74(1)
3.8 Saturated Adiabatic Lapse Rate
75(2)
3.9 Pollution Dispersion---Screening Model
77(1)
3.10 Pollution Dispersion---Gaussian Plume
78(3)
3.11 Vertical Distribution
81(2)
3.12 Momentum and Buoyancy
83(2)
3.13 Wind Speed Variations
85(2)
3.14 Water Pollution Modelling
87(1)
3.15 Types of Water Pollution
88(2)
3.16 Water Quality Treatment
90(1)
3.17 Water Pollution Statistics
90(2)
3.18 Mass Balance Equations
92(1)
3.19 Advection-Dispersion Transport
93(3)
3.20 Advection Transport
96(2)
3.21 Conclusion
98(3)
References
98(3)
4 Harvesting Energy from Ambient Sources: Wind Energy, Hydropower, Radiation and Mechanical Deformation
101(34)
4.1 Introduction
101(2)
4.2 Ambient Sources
103(2)
4.3 Wind Energy
105(6)
4.4 Hydropower
111(3)
4.5 Photodiodes
114(6)
4.6 Radiation Sources
120(5)
4.7 Piezoelectric Energy
125(7)
4.8 Microelectromechanical Structures
132(1)
4.9 Conclusion
133(2)
References
133(2)
5 The Sub-systems of an Energy Harvesting Device: Focus on RFID Fundamentals
135(30)
5.1 Introduction
135(1)
5.2 Radio-Frequency Identification
136(4)
5.3 Sub-system Definitions
140(1)
5.4 Antenna
140(2)
5.5 Rectifier Circuits
142(4)
5.6 Regulator Circuits (Low Dropout Regulator)
146(4)
5.7 Amplifier Circuits
150(6)
5.8 Matching Networks
156(4)
5.9 Energy Storage
160(2)
5.10 Conclusion
162(3)
6 Geographic Information Systems and Remote Sensing
165(36)
6.1 Introduction
165(1)
6.2 Spatial Technologies
166(1)
6.3 Geographic Information System
167(1)
6.4 GIS Projects in Africa
168(2)
6.4.1 Zambia
168(1)
6.4.2 Uganda
169(1)
6.4.3 Kenya
169(1)
6.4.4 Rwanda
169(1)
6.4.5 South Africa
170(1)
6.4.6 Botswana
170(1)
6.5 Computational Geometry
170(3)
6.6 Geographic Maps
173(2)
6.7 Geographic Data
175(14)
6.8 Global Positioning System
189(4)
6.9 Remote Sensing
193(6)
6.10 Conclusion
199(2)
References
199(2)
7 Ubiquitous Computing: Distributing Mobile Computing to Build a Global Network of Things
201(36)
7.1 Introduction
201(2)
7.2 Distributed Computing
203(5)
7.3 Mobile Computing
208(1)
7.4 Evolution of Pervasive Computing
208(2)
7.5 RFID in Ubiquitous Technology
210(1)
7.6 Software in Pervasive Computing Applications
210(2)
7.7 Human-Centered Pervasive Computing System Model
212(2)
7.8 Pervasive Computing: Thematic Guidelines
214(4)
7.9 Situated Social Context
218(2)
7.10 Pervasive Social Computing
220(3)
7.11 Social Computing Challenges
223(1)
7.12 Pervasive Service Computing
224(2)
7.13 Pervasive Computing in Developing Countries
226(2)
7.14 Pervasive Computing Challenges in Developing Countries
228(5)
7.15 Conclusion
233(4)
References
234(3)
8 Designing and Planning for Sustainable Urbanism with Focus on Developing Countries
237(32)
8.1 Introduction
237(3)
8.2 United Nations Millennium Development Goals (2015 Update)
240(1)
8.3 Sustainable Resources
241(2)
8.4 Responsible Development
243(8)
8.5 Impact Assessment
251(4)
8.6 Social and Economic Metrics
255(3)
8.7 Demographic Considerations
258(3)
8.8 Urban Macro-Effects
261(4)
8.9 Environmental Impact Metrics
265(1)
8.10 Conclusion
266(3)
References
268(1)
9 Tools and Facilitators Towards Successful Planning for Sustainable Cities
269(38)
9.1 Introduction
269(1)
9.2 Population Growth
270(8)
9.3 Smart Cities
278(4)
9.4 Pollution
282(7)
9.5 Ambient Sources and Energy Harvesting
289(6)
9.6 GIS, Remote Sensing and Ubiquitous Computing
295(6)
9.7 Environmental Impact of Climate Change
301(3)
9.8 Conclusion
304(3)
References
305(2)
10 Case Studies: Developing Countries Committed to an Ecologically Aware Future
307
10.1 Introduction
307(1)
10.2 Categories of Sustainable Development
308(7)
10.3 Indicators of Sustainable Cities
315(8)
10.4 Sustainable City Rankings
323(3)
10.5 Worldwide Smart City Initiatives
326(6)
10.5.1 South Africa---Human Capital in ICT, Information Distribution and Transport
326(1)
10.5.2 South Africa---Local Municipal Energy Conservation Efforts
326(1)
10.5.3 Italy---Training Programs in Theoretical Physics Aimed at Creating Environmentally Aware and Therefore Sustainable Communities in Developing Countries
327(1)
10.5.4 North Africa---Consultation Towards Smart Initiatives
328(1)
10.5.5 China---Successful Smart Integration by Provincial Governments
328(1)
10.5.6 United Kingdom---Strategy to Lower Carbon Emissions Due to Energy Usage
329(1)
10.5.7 Brazil---Focus on Water and Sanitation Distribution
329(1)
10.5.8 Joint European Initiative---Financial Research Conducted in Europe to Support Smart and Sustainable Cities
330(1)
10.5.9 Sweden---Best Practice in Mixed Use of Environmental Adaption in Urban Areas
331(1)
10.6 Noteworthy Reports of Smart and Sustainable Technologies
332(3)
10.6.1 Wireless Sensor Networks to Monitor Food Sustainability (Libelium, 28 February 2012)
332(1)
10.6.2 Google's® Pollution Sensing Gear in Street View Cars (Engadget, July 30th 2015)
333(1)
10.6.3 International Space Station Photos Map Light Pollution
334(1)
10.6.4 Samsung's Earth-Wide Internet Through 4600 Satellites (Engadget, 17 August 2015)
334(1)
10.6.5 Google Brings Android® One® Devices to Africa (Engadget, August 18th 2015)
334(1)
10.6.6 Malaysia Will Use RFID to Track Vehicles (Engadget, 26 August 2015)
335(1)
10.6.7 Phone Data Can Predict Infectious Disease Outbreaks (Engadget, 30 August 2015)
335(1)
10.7 The United Nations Sustainable Development Summit 2015
335(3)
10.8 Conclusion
338
References
338
Saurabh Sinha obtained his Ph.D. degree in Electronic Engineering from the University of Pretoria, South Africa. He has authored or co-authored over 85 publications in peer-reviewed journals and at international conferences. In addition, he is the managing editor of the South African Institute of Electrical Engineers (SAIEE) Africa Research Journal. Prof. Sinha served University of Pretoria for over a decade, his last service being as Director of the Carl and Emily Fuchs Institute for Microelectronics. Since 2013 he has been Executive Dean of the Faculty of Engineering and Built Environment at the University of Johannesburg. He was the 2014-2015 Vice-President, IEEE Educational Activities and serves on the IEEE Board of Directors.
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