CONTENTS:
INTRO
WHAT IS A SMART CITY
GEOSPATIAL TECHNOLOGY
WIRELESS SENSOR NETWORKS
SENSORS & STANDARDS
AD-HOC NETWORKS
SMART CITY SURVEILLANCE
A.I
GEOFENCING & GEOLOCATION
INTERNET OF VEHICLES
SMART HOME
THE BODY AREA NETWORKS
INSIGHT
INTRO
WHAT IS A SMART CITY
GEOSPATIAL TECHNOLOGY
WIRELESS SENSOR NETWORKS
SENSORS & STANDARDS
AD-HOC NETWORKS
SMART CITY SURVEILLANCE
A.I
GEOFENCING & GEOLOCATION
INTERNET OF VEHICLES
SMART HOME
THE BODY AREA NETWORKS
INSIGHT
Intro
The Smart city and IoT framework is a "dual system" of advanced technology merging that is both beneficial and harmful:
On one hand, it promises quality of life through advanced technological integrations, sustainable energy solutions, intelligent traffic systems and real-time data analysis.
On the other hand, the same system harbors potential pitfalls, threatening individual privacy, opening doors to cyber vulnerabilities that are one way or another detrimental to humans.
The Electromagnetic Spectrum
Mobile networks like 3G, 4G, and 5G not only operate within the electromagnetic spectrum but are directly correlated with the development of the smart city and IoT frameworks, each using different frequency bands to transmit data wirelessly. With each generational leap, there's a notable enhancement in capabilities:
3G had basic IoT applications, introduced mobile data services allowing basic internet access, video calls, and the onset of mobile broadband.
4G laid the groundwork for more complex IoT deployments, due to its improved speed and reliability,
5G has the ability to handle the connectivity needs of countless sensors and devices involved in traffic management, environmental monitoring, public safety, and more.
Looking towards 6G, the promise is even more transformative, with potential for global coverage, even lower latency, and emerging technologies.
1. Electromagnetic Spectrum: Applications, Regions, and Impact on Technology and Health
https://openmedscience.com/electromagnetic-spectrum-applications-regions-and-impact-on-technology-and-health/
2. Generations of Mobile Networks: Evolution from 1G to 5G
https://tridenstechnology.com/generations-of-mobile-networks/
3. 5G Technology: Unleashing the Power of Ultra-Fast Wireless Connectivity
https://fpgainsights.com/wireless-networking/5g-technology-the-power-of-ultra-fast-wireless-connectivity/
https://openmedscience.com/electromagnetic-spectrum-applications-regions-and-impact-on-technology-and-health/
2. Generations of Mobile Networks: Evolution from 1G to 5G
https://tridenstechnology.com/generations-of-mobile-networks/
3. 5G Technology: Unleashing the Power of Ultra-Fast Wireless Connectivity
https://fpgainsights.com/wireless-networking/5g-technology-the-power-of-ultra-fast-wireless-connectivity/
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1. NASA Introduction to the ElectroMagneticSpectrum https://science.nasa.gov/ems/01_intro/ 2.ITU Emf Guide / Mobile Networks https://www.itu.int/net4/mob/ituemf/en/emfguide_m.html |
What is a Smart city and the Internet of things ( IoT ) ?
A smart city leverages technology to enhance urban living by integrating various systems like transportation, utilities, and public services into a cohesive network. Central to this concept is the Internet of Things (IoT), which consists of interconnected devices and sensors that collect and share data in real-time. This connectivity allows for more efficient resource management, improved public safety, and enhanced quality of life through innovations like smart grids, intelligent traffic management, and responsive public services. Essentially, IoT forms the backbone of a smart city by enabling the seamless interaction and automation of city functions.
Introduction to IEEE Internet of Things (IOT) and Smart Cities
https://standards.ieee.org/wp-content/uploads/import/documents/other/geps_07-iot_smart_cities.pdf
The United Nations Smart city overview in line with the sustainable development goals.
1. U.N Smarter and Inclusive cities. Big overview
https://www.undp.org/sites/g/files/zskgke326/files/2024-06/smarterandinclusivecitiescourse_2.pdf U.N Smart cities Supporting an Inclusive, Sustainable, and Resilient Society. short overview https://unosd.un.org/sites/unosd.un.org/files/session_10-3_mr._kazushige_endo.pdf |
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The World Economic Forum (WEF) Smart City overview
1. 4 ways smart cities will make our lives better https://www.weforum.org/stories/2016/02/4-ways-smart-cities-will-make-our-lives-better/
Anatomy of a smart city https://www.weforum.org/stories/2019/01/the-anatomy-of-a-smart-city/ |
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The International Telecommunication Union (ITU) Smart City overview
1. Implementing ITU-T International Standards to Shape Smart Sustainable Cities https://www.uncclearn.org/wp-content/uploads/library/the_case_of_moscow-e_18-00503_itu.pdf SMART CULTURAL HERITAGE IN DIGITAL CITIES UN and ITU https://sdct-journal.com/images/Issues/2018_1b/25-32.pdf |
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The Institute of Electrical and Electronics Engineers (IEEE) smart city overview and smart standards
1. IEEE SMART CITIES https://smartcities.ieee.org/ IEEE Standards Activities for Smart Cities https://standards.ieee.org/wp-content/uploads/import/documents/other/smartcities.pdf |
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Geospatial technology refers to the suite of tools and techniques used to gather, analyze, and display geographical data, including Geographic Information Systems (GIS), remote sensing, and Global Positioning Systems (GPS). In the context of smart cities, geospatial technology plays a crucial role by providing a framework for integrating spatial data into urban planning and governance. Here's how:
Smart City Framework: This technology is vital within smart cities, integrating spatial data into urban planning and management processes.
Urban Management: It enables real-time mapping and monitoring of various urban elements such as population, infrastructure, environmental conditions, and traffic flow.
Resource Optimization: Enhances the efficiency of public services, transportation systems, and utility management like water and energy.
Emergency Response: Provides precise location data for quicker and more effective responses to emergencies.
Sustainability and Resilience: Supports sustainable urban development, improving the quality of life and making urban environments more resilient to future challenges.
Smart City Framework: This technology is vital within smart cities, integrating spatial data into urban planning and management processes.
Urban Management: It enables real-time mapping and monitoring of various urban elements such as population, infrastructure, environmental conditions, and traffic flow.
Resource Optimization: Enhances the efficiency of public services, transportation systems, and utility management like water and energy.
Emergency Response: Provides precise location data for quicker and more effective responses to emergencies.
Sustainability and Resilience: Supports sustainable urban development, improving the quality of life and making urban environments more resilient to future challenges.
Privacy Concerns with Geospatial Data
https://biomedware.com/privacy-concerns-geospatial-data/
Navigating security challenges in the digital age
https://www.infosysbpm.com/blogs/geospatial-data-services/geospatial-data-privacy-navigating-security-challenges-in-the-digital-age.html
Geospatial technology for smart cities: Understanding Geospatial Technologies for Future City Management
https://biblus.accasoftware.com/en/geospatial-technology-for-smart-cities/
Achieving Sustainable Smart Cities through Geospatial Data-Driven Approaches
https://www.mdpi.com/2071-1050/16/2/640
https://biomedware.com/privacy-concerns-geospatial-data/
Navigating security challenges in the digital age
https://www.infosysbpm.com/blogs/geospatial-data-services/geospatial-data-privacy-navigating-security-challenges-in-the-digital-age.html
Geospatial technology for smart cities: Understanding Geospatial Technologies for Future City Management
https://biblus.accasoftware.com/en/geospatial-technology-for-smart-cities/
Achieving Sustainable Smart Cities through Geospatial Data-Driven Approaches
https://www.mdpi.com/2071-1050/16/2/640
Geo Spacial World https://geospatialworld.net/blogs/role-of-gis-in-the-journey-of-smart-cities/ |
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The Wireless Sensor Networks
The Wireless Sensor Networks (WSNs) are integral for collecting real-time data on a multitude of urban metrics like air quality, traffic flow, and energy use in the Smart and Iot framework. These networks are composed of many small, low-power sensors that autonomously gather information and transmit it wirelessly to central systems for processing. Within the IoT framework, this data is used to drive automation, predictive maintenance, and adaptive urban management. By integrating WSNs, cities can dynamically adjust services such as public transportation, waste collection, and street lighting to current conditions, thereby improving efficiency and sustainability. However, WSNs also have significant drawbacks :
Privacy concerns are paramount, as these networks continuously collect data that could potentially be used to monitor individual behaviors or movements.
WSNs are vulnerable to cyber, attacks which could compromise data integrity or lead to service disruptions.
The reliability of data can be affected by interference, range limitations, or sensor failures, potentially leading to inaccurate information or system inefficiencies.
Privacy concerns are paramount, as these networks continuously collect data that could potentially be used to monitor individual behaviors or movements.
WSNs are vulnerable to cyber, attacks which could compromise data integrity or lead to service disruptions.
The reliability of data can be affected by interference, range limitations, or sensor failures, potentially leading to inaccurate information or system inefficiencies.
Wireless sensor network
https://en.wikipedia.org/wiki/Wireless_sensor_network
Wireless Sensor Networks for Smart Cities: Network Design, Implementation and Performance Evaluation
https://www.mdpi.com/2079-9292/10/2/218
Wireless Sensor Networks Challenges and Solutions
https://www.intechopen.com/chapters/86241
IEEE Wireless Sensor networks Projects, attacks and solutions
https://phdtopic.com/ieee-wireless-sensor-networks-projects/
https://en.wikipedia.org/wiki/Wireless_sensor_network
Wireless Sensor Networks for Smart Cities: Network Design, Implementation and Performance Evaluation
https://www.mdpi.com/2079-9292/10/2/218
Wireless Sensor Networks Challenges and Solutions
https://www.intechopen.com/chapters/86241
IEEE Wireless Sensor networks Projects, attacks and solutions
https://phdtopic.com/ieee-wireless-sensor-networks-projects/
Wireless Sensor Network (WSN) protocols are designed to manage communication between sensor nodes, focusing on energy efficiency, data routing, and reliability within constraints like limited power and bandwidth. These protocols balance the need for timely data transmission with the necessity for low energy consumption, often using methods like data aggregation and adaptive routing.Here are some standard network communications often employed in WSNs:
Zigbee: Based on IEEE 802.15.4, it's ideal for home automation and industrial applications with its low-power mesh networking.
Bluetooth Low Energy (BLE): Perfect for short-range, low-power applications, especially in personal health monitoring and wearables, with support for mesh networking.
LoRaWAN: Provides long-range communication with very low power consumption, suitable for wide-area applications like environmental monitoring.
Sigfox: Another LPWAN technology, known for ultra-low power consumption and long-range connectivity, often used for IoT applications like asset tracking.
LTE (NB-IoT and LTE-M): Cellular-based solutions offering connectivity with different trade-offs between range, power, and data rate for various IoT needs.
Wi-Fi: Typically used for higher data rate applications within shorter ranges, can be power-intensive but useful for certain WSN scenarios.
Zigbee: Based on IEEE 802.15.4, it's ideal for home automation and industrial applications with its low-power mesh networking.
Bluetooth Low Energy (BLE): Perfect for short-range, low-power applications, especially in personal health monitoring and wearables, with support for mesh networking.
LoRaWAN: Provides long-range communication with very low power consumption, suitable for wide-area applications like environmental monitoring.
Sigfox: Another LPWAN technology, known for ultra-low power consumption and long-range connectivity, often used for IoT applications like asset tracking.
LTE (NB-IoT and LTE-M): Cellular-based solutions offering connectivity with different trade-offs between range, power, and data rate for various IoT needs.
Wi-Fi: Typically used for higher data rate applications within shorter ranges, can be power-intensive but useful for certain WSN scenarios.
1. Global Wireless Sensor Networks for smart technologies file:///C:/Users/OEM/Downloads/DataAnalysisandOutlierDetectioninSmartCity.pdf
2. AIOTI STANDARDISATION OUTLOOK, IEEE, ISO, IEC, ETC https://aioti.eu/wp-content/uploads/2023/01/AIOTI-SDOs-Alliance-Landscape-IoT-LSP-standards-framework-R3-Final.pdf 3.IoT-Enabled Smart Sustainable Cities: Challenges and Approaches https://www.mdpi.com/2624-6511/3/3/52 4.Different wireless sensor network topologies. file:///C:/Users/OEM/Downloads/Advances_in_Information_Provision_from_Wireless_Se-1.pdf |
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In a Smart City, an array of sensors are embedded ubiquitously to monitor everything from traffic flow to environmental conditions. These include traffic sensors, light and motion detectors in street lamps, air quality detectors, smart meters for utilities, and nanosensors for detailed environmental or health monitoring. Communication among these sensors typically occurs via the Wireless Sensor networks. This pervasive sensor network not only helps in making informed decisions but also supports predictive maintenance and planning, ensuring that the city evolves in a sustainable and human-centric manner. However, the omnipresence of these sensors introduces significant privacy and security challenges opening avenues for misuse. Real-time monitoring means that data about individuals' movements, behaviors, and even health can be collected constantly, potentially without explicit consent, turning the smart environment into an inadvertent surveillance hub if not properly secured.
Sensors on Internet of Things Systems for the Sustainable Development of Smart Cities: A Systematic Literature Review
https://pmc.ncbi.nlm.nih.gov/articles/PMC11014400/
The Role of Advanced Sensing in Smart Cities
https://pmc.ncbi.nlm.nih.gov/articles/PMC3574682/
Designer’s guide for deploying sensors in smart cities
https://www.electronicproducts.com/designers-guide-for-deploying-sensors-in-smart-cities/
https://pmc.ncbi.nlm.nih.gov/articles/PMC11014400/
The Role of Advanced Sensing in Smart Cities
https://pmc.ncbi.nlm.nih.gov/articles/PMC3574682/
Designer’s guide for deploying sensors in smart cities
https://www.electronicproducts.com/designers-guide-for-deploying-sensors-in-smart-cities/
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1.Enabling Communication Technologies for Smart Cities https://www.researchgate.net/publication/309210290_Enabling_Communication_Technologies_for_Smart_Cities 2.Networking Architectures and Protocols for IoT Applications in Smart Cities: Recent Developments and Perspectives https://www.mdpi.com/2079-9292/12/11/2490 |
Wireless ad-hoc networks play a significant role in the smart and IoT frameworks by enabling devices to communicate autonomously without relying on a fixed infrastructure. This autonomy is crucial for environments where devices need to dynamically connect and share data, enhancing functionality and efficiency like in smart homes, cities, or industries. Different types of ad-hoc networks serve specific needs:
Mobile Ad-Hoc Networks (MANETs) are used where device mobility is high, such as in military or emergency response scenarios, allowing devices like smart phones to form networks on the fly.
Wireless Sensor Networks (WSNs) deploy numerous sensors to monitor physical conditions, agriculture, environmental monitoring, or industrial control where sensor nodes can communicate directly or through a network.
Flying Ad-Hoc Networks (FANET) is an ad hoc network with aircraft as nodes that can be used for communication between unmanned aerial vehicles (UAVs) and a ground control station (GCS).
Vehicle Ad-Hoc Networks (VANETs) are designed for communication between vehicles (V2V) and between vehicles and infrastructure (V2I), improving traffic management and safety.
Visible Light Ad hoc Networks (VLANET) Visible Light Communication is a subset of telecommunications technology that transmits data using the visible electromagnetic spectrum
Though ad-hoc networks prove beneficial, hacking attacks pose significant threats due to their decentralized and dynamic nature:
1. Eavesdropping: data can be easily intercepted by attackers who are within range. This passive attack violates confidentiality, particularly if the data transmitted is not encrypted.
2. Man-in-the-Middle (MITM) Attack: An attacker can position themselves between two communicating nodes, intercepting, altering, or inserting false messages. This can be particularly deceptive, leading to corrupted data or unauthorized access.
3. Denial-of-Service (DoS) Attack: By flooding the network with unnecessary traffic or by targeting specific nodes with resource exhaustion attacks, an attacker can prevent legitimate use of the network, making services unavailable to its intended users.
4. Black hole/Sinkhole Attack: Malicious nodes advertise themselves as having the shortest path to the destination node, attracting all traffic. Once the traffic is routed through the malicious node, it can drop or alter the packets.
5. Impersonation: By spoofing the identity of a legitimate node, attackers can deceive other nodes into sending data or routing through them, compromising the network's integrity.
Mobile Ad-Hoc Networks (MANETs) are used where device mobility is high, such as in military or emergency response scenarios, allowing devices like smart phones to form networks on the fly.
Wireless Sensor Networks (WSNs) deploy numerous sensors to monitor physical conditions, agriculture, environmental monitoring, or industrial control where sensor nodes can communicate directly or through a network.
Flying Ad-Hoc Networks (FANET) is an ad hoc network with aircraft as nodes that can be used for communication between unmanned aerial vehicles (UAVs) and a ground control station (GCS).
Vehicle Ad-Hoc Networks (VANETs) are designed for communication between vehicles (V2V) and between vehicles and infrastructure (V2I), improving traffic management and safety.
Visible Light Ad hoc Networks (VLANET) Visible Light Communication is a subset of telecommunications technology that transmits data using the visible electromagnetic spectrum
Though ad-hoc networks prove beneficial, hacking attacks pose significant threats due to their decentralized and dynamic nature:
1. Eavesdropping: data can be easily intercepted by attackers who are within range. This passive attack violates confidentiality, particularly if the data transmitted is not encrypted.
2. Man-in-the-Middle (MITM) Attack: An attacker can position themselves between two communicating nodes, intercepting, altering, or inserting false messages. This can be particularly deceptive, leading to corrupted data or unauthorized access.
3. Denial-of-Service (DoS) Attack: By flooding the network with unnecessary traffic or by targeting specific nodes with resource exhaustion attacks, an attacker can prevent legitimate use of the network, making services unavailable to its intended users.
4. Black hole/Sinkhole Attack: Malicious nodes advertise themselves as having the shortest path to the destination node, attracting all traffic. Once the traffic is routed through the malicious node, it can drop or alter the packets.
5. Impersonation: By spoofing the identity of a legitimate node, attackers can deceive other nodes into sending data or routing through them, compromising the network's integrity.
Wireless ad hoc network
https://en.wikipedia.org/wiki/Wireless_ad_hoc_network
Moving Ad Hoc Networks—A Comparative Study
https://www.mdpi.com/2071-1050/13/11/6187
Different types of attacks in Mobile ADHOC Network: Prevention and mitigation techniques
https://arxiv.org/pdf/1111.4090
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1. Wireless sensor network https://www.researchgate.net/figure/A-typical-sensor-network-architecture_fig1_286733183 2. Mobile adhoc network 3. Vanet Vehicular adhoc 4. Fanet Flying Adhoc 5. Vlanet Visable light Adhoc A Comparative Study of Ad Hoc Networks https://www.researchgate.net/publication/377414030_A_Comparative_Study_of_Ad_Hoc_Networks |
Ubiquitous smart city surveillance, including CCTV cameras, cameras placed throughout the city, Unmanned Aerial Vehicles (UAVs or drones) for monitoring, presents both advantages and drawbacks:
Positive Traits:
Public Safety: These systems can significantly reduce crime rates by deterring potential criminal activities and providing evidence post-incident.
Traffic Management: Cameras can help in real-time traffic control, accident response, and congestion management, improving urban mobility.
Emergency Response: Drones can be deployed for search and rescue, monitoring natural disasters, or providing an aerial view during crises.
Negative Traits:
Privacy Concerns: The omnipresence of cameras can lead to a surveillance state feeling, where individuals feel constantly watched, potentially chilling free behavior or expression.
Hacking: Exploiting software weaknesses to gain unauthorized access.
Insider Threats: Abuse or misuse by personnel with access.
Data Security: With more cameras comes more data, raising questions about how this data is stored, protected, and who has access to it. Misuse or breaches could lead to significant privacy violations.
Malware: Infecting devices via malicious software updates or links.
Abuse Potential: There's always the risk of surveillance tools being used for purposes not intended by law, such as unauthorized monitoring of individuals.
Positive Traits:
Public Safety: These systems can significantly reduce crime rates by deterring potential criminal activities and providing evidence post-incident.
Traffic Management: Cameras can help in real-time traffic control, accident response, and congestion management, improving urban mobility.
Emergency Response: Drones can be deployed for search and rescue, monitoring natural disasters, or providing an aerial view during crises.
Negative Traits:
Privacy Concerns: The omnipresence of cameras can lead to a surveillance state feeling, where individuals feel constantly watched, potentially chilling free behavior or expression.
Hacking: Exploiting software weaknesses to gain unauthorized access.
Insider Threats: Abuse or misuse by personnel with access.
Data Security: With more cameras comes more data, raising questions about how this data is stored, protected, and who has access to it. Misuse or breaches could lead to significant privacy violations.
Malware: Infecting devices via malicious software updates or links.
Abuse Potential: There's always the risk of surveillance tools being used for purposes not intended by law, such as unauthorized monitoring of individuals.
Involvement of Surveillance Drones in Smart Cities: A Systematic Review
https://ieeexplore.ieee.org/document/9781426
Airborne Drones describe "Drones and the Smart City"
https://nextech.online/smart-city/?utm_source=direct&utm_medium=direct
https://ieeexplore.ieee.org/document/9781426
Airborne Drones describe "Drones and the Smart City"
https://nextech.online/smart-city/?utm_source=direct&utm_medium=direct
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1. A Survey of Video Surveillance Systems in Smart City
https://www.mdpi.com/2079-9292/12/17/3567 2.Review of the application of drones for smart cities https://www.researchgate.net/publication/385320360_Review_of_the_application_of_drones_for_smart_cities |
A.I Integration with Smart Surveillance:
Positive Traits:
Efficiency: AI can analyze vast amounts of data from sensors and cameras to identify patterns, optimize city operations, predict maintenance needs, or detect anomalies that might require immediate action.
Personalization: AI can tailor public services based on real-time data, enhancing user experience in areas like transportation or public health notifications.
Safety and Security: AI algorithms can help in identifying potential security threats or in crowd management during events, potentially preventing incidents before they escalate.
Negative Traits:
Privacy Invasion: AI's ability to process and interpret data means that even more detailed insights into personal behaviors can be drawn from ubiquitous surveillance, leading to concerns about profiling, discrimination, or manipulation.
Bias and Errors: If not carefully designed and monitored, AI systems can perpetuate or even exacerbate biases, leading to unfair surveillance or decision-making that disproportionately impacts certain groups.
Autonomy and Control: With AI potentially making autonomous decisions based on surveillance data, there's a risk of reducing human oversight, which could lead to ethical dilemmas or misuse by those in control of the systems.
Positive Traits:
Efficiency: AI can analyze vast amounts of data from sensors and cameras to identify patterns, optimize city operations, predict maintenance needs, or detect anomalies that might require immediate action.
Personalization: AI can tailor public services based on real-time data, enhancing user experience in areas like transportation or public health notifications.
Safety and Security: AI algorithms can help in identifying potential security threats or in crowd management during events, potentially preventing incidents before they escalate.
Negative Traits:
Privacy Invasion: AI's ability to process and interpret data means that even more detailed insights into personal behaviors can be drawn from ubiquitous surveillance, leading to concerns about profiling, discrimination, or manipulation.
Bias and Errors: If not carefully designed and monitored, AI systems can perpetuate or even exacerbate biases, leading to unfair surveillance or decision-making that disproportionately impacts certain groups.
Autonomy and Control: With AI potentially making autonomous decisions based on surveillance data, there's a risk of reducing human oversight, which could lead to ethical dilemmas or misuse by those in control of the systems.
IEEE Smart Cities https://smartcities.ieee.org/component/search/?searchword=ARTIFICIAL%20INTELLIGENCE%20SMART%20CITY&ordering=popular&searchphrase=any
These five cities are making innovative use of generative AI https://www.weforum.org/stories/2024/07/generative-ai-smart-cities/
How AI and Machine Learning help build a Smart City? https://www.esds.co.in/blog/how-ai-and-machine-learning-help-build-a-smart-city/
These five cities are making innovative use of generative AI https://www.weforum.org/stories/2024/07/generative-ai-smart-cities/
How AI and Machine Learning help build a Smart City? https://www.esds.co.in/blog/how-ai-and-machine-learning-help-build-a-smart-city/
1. Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trends
https://www.mdpi.com/1424-8220/23/11/5206 Artificial intelligence across industries - IEC Whitepaper https://www.researchgate.net/publication/329191549_Artificial_intelligence_across_industries_-_IEC_Whitepaper |
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Geofencing and Geolocation technologies can be particularly exploited in smart cities. Geofencing, which involves creating virtual boundaries for triggering specific actions, can be used for targeted marketing or security but also for unwarranted tracking of individuals' movements. Geolocation, which identifys the geographic location of a device or user usually through the use of IP addresses, GPS, Wi-Fi signals, or cell tower data, can similarly be abused.
Geolocation vs Geofencing: Understand the Difference
https://timecentral.co/blog/geolocation-vs-geofencing-understand-the-difference/
How Geofencing Technology Is Helping In Smart City Developments
https://www.conurets.com/how-geofencing-technology-is-helping-in-smart-city-developments/
What is Geofencing? and how does i improve my Smart Home Security System?
https://alarmsys.com/what-is-geofencing-and-how-does-it-improve-my-smart-home-security-system/
https://timecentral.co/blog/geolocation-vs-geofencing-understand-the-difference/
How Geofencing Technology Is Helping In Smart City Developments
https://www.conurets.com/how-geofencing-technology-is-helping-in-smart-city-developments/
What is Geofencing? and how does i improve my Smart Home Security System?
https://alarmsys.com/what-is-geofencing-and-how-does-it-improve-my-smart-home-security-system/
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What is Geofencing and How Does it Works? https://www.youtube.com/watch?v=AlnYmT22_Mg |
The Internet of Vehicles (IoV) refers to the network of connected vehicles and infrastructure that communicate to enhance transportation efficiency, safety, and convenience. Vehicles to everything (V2X), Vehicles exchange data with each other (V2V), with road infrastructure (V2I), with the cloud (V2C) and with people (V2P) for real-time-traffic management, accident prevention, and improved navigation. However IoV can be exploited in various ways:
Data Privacy: Vehicles can collect vast amounts of data about driving habits, locations visited, and even personal conversations. If this data is not securely managed, it can lead to privacy breaches. Communication between vehicles or with infrastructure could be intercepted or tampered with.
Cyber security Threats: Connected cars can be targets for hacking, with risks ranging from data theft to taking control of vehicle functions like brakes or steering. Malicious actors could exploit vulnerabilities in vehicle software or connected systems.
Surveillance: With vehicles acting as mobile sensors, they could be used for tracking individuals or gathering data for unauthorized purposes.
Malware: Vehicles could be infected with malware through connected devices or updates.
Denial-of-Service (DoS): Overloading communication networks to disrupt vehicle operations.
Data Privacy: Vehicles can collect vast amounts of data about driving habits, locations visited, and even personal conversations. If this data is not securely managed, it can lead to privacy breaches. Communication between vehicles or with infrastructure could be intercepted or tampered with.
Cyber security Threats: Connected cars can be targets for hacking, with risks ranging from data theft to taking control of vehicle functions like brakes or steering. Malicious actors could exploit vulnerabilities in vehicle software or connected systems.
Surveillance: With vehicles acting as mobile sensors, they could be used for tracking individuals or gathering data for unauthorized purposes.
Malware: Vehicles could be infected with malware through connected devices or updates.
Denial-of-Service (DoS): Overloading communication networks to disrupt vehicle operations.
Internet of Vehicles wikipedia https://en.wikipedia.org/wiki/Internet_of_vehicles
V2X Vehicle to everything https://www.litepoint.com/wp-content/uploads/2019/05/V2X-051619.pdf
A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches
https://ieeexplore.ieee.org/document/9716935
V2X Vehicle to everything https://www.litepoint.com/wp-content/uploads/2019/05/V2X-051619.pdf
A Survey of VANET/V2X Routing From the Perspective of Non-Learning- and Learning-Based Approaches
https://ieeexplore.ieee.org/document/9716935
1. Internet of Vehicles (IOV) | Smart City ,IOT IOB VANETs, Artificial Intelligence https://www.youtube.com/watch?v=WhdBgnCKG4o |
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The Smart home can transform into a tool for illegal surveillance, where malicious actors could access cameras, microphones, or manipulate devices like fridges or door locks. If one device is hacked, it can act as a gateway for attackers to compromise other connected devices. This happens because they often share the same network, and vulnerabilities leading to widespread security breaches across the entire smart home network:
Smart Appliances: Hackers might gain access through default or weak passwords, outdated software, or insecure network connections. Once inside, they could spy through connected cameras, listen via microphones, or even manipulate appliances to cause physical harm, like overheating a stove or unlocking doors.
Malware: Infecting devices via malicious software updates or links.
Risk to Human Occupants:
Privacy Invasion: Unauthorized surveillance of home activities, conversations, or routines could lead to personal data breaches or blackmail.
Physical Safety: Manipulation of home systems could result in dangerous situations, such as turning off security systems, altering thermostat settings to extreme temperatures, or controlling access to the home.
Smart Appliances: Hackers might gain access through default or weak passwords, outdated software, or insecure network connections. Once inside, they could spy through connected cameras, listen via microphones, or even manipulate appliances to cause physical harm, like overheating a stove or unlocking doors.
Malware: Infecting devices via malicious software updates or links.
Risk to Human Occupants:
Privacy Invasion: Unauthorized surveillance of home activities, conversations, or routines could lead to personal data breaches or blackmail.
Physical Safety: Manipulation of home systems could result in dangerous situations, such as turning off security systems, altering thermostat settings to extreme temperatures, or controlling access to the home.
How IoT devices, even washing machines, can be used for hacking
https://www.nemko.com/blog/how-iot-devices-even-washing-machines-can-be-used-for-hacking
The digital harms of smart home devices A systematic literature review
https://www.sciencedirect.com/science/article/pii/S0747563223001218
Smart Homes, cities and energy
https://www.uc.edu/content/dam/refresh/cont-ed-62/olli/22-winter/future%20smart%20cities%20homes%20energy.pdf
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1. Fostering new vertical and horizontal IoT applications with intelligence everywhere
https://www.researchgate.net/publication/374820809_Fostering_new_vertical_and_horizontal_IoT_applications_with_intelligence_everywhere 2. Cyber-Security of Embedded IoTs in Smart Homes: Challenges, Requirements, Countermeasures, and Trends https://ieeexplore.ieee.org/document/10005800 |
The Body Area Networks (BANs) are pivotal in advancing telehealth, offering significant benefits for remote healthcare:
Telehealth: BANs facilitate the continuous monitoring of vital signs and health metrics, enabling doctors to make informed decisions remotely. This technology supports telemedicine by providing real-time, accurate health data, which is crucial for managing chronic conditions, post-surgical care, or elderly care without the need for frequent hospital visits. The beneficial applications of telehealth are numerous however this advancement also comes with high risks such as hacking into devices like smart pacemakers or insulin pumps that could lead to life-threatening situations by altering medication delivery, heart rhythm control, or any other invasive sinister attacks.
Data Breach: could lead to unauthorized access of personal health information or other sensitive data transmitted between devices like sensors, wearables, and medical implants. This can lead to privacy violations or health risks if the data is misused or altered .
Telehealth: BANs facilitate the continuous monitoring of vital signs and health metrics, enabling doctors to make informed decisions remotely. This technology supports telemedicine by providing real-time, accurate health data, which is crucial for managing chronic conditions, post-surgical care, or elderly care without the need for frequent hospital visits. The beneficial applications of telehealth are numerous however this advancement also comes with high risks such as hacking into devices like smart pacemakers or insulin pumps that could lead to life-threatening situations by altering medication delivery, heart rhythm control, or any other invasive sinister attacks.
Data Breach: could lead to unauthorized access of personal health information or other sensitive data transmitted between devices like sensors, wearables, and medical implants. This can lead to privacy violations or health risks if the data is misused or altered .
Below is the computer network types by scale starting from the Nano, followed by the Body area networks ( BAN ) and so on.
1. Body area network wikipedia https://en.wikipedia.org/wiki/Body_area_network
2. A Comprehensive Survey of Wireless Body Area Networks
https://www.researchgate.net/publication/45709672_A_Comprehensive_Survey_of_Wireless_Body_Area_Networks
3. Wearable Wireless Body Area Networks for Medical Applications
https://onlinelibrary.wiley.com/doi/10.1155/2021/5574376
4.Moving Towards Body-to-Body Sensor Networks for Ubiquitous Applications: A Survey
https://www.mdpi.com/2224-2708/8/2/27
1. Body area network wikipedia https://en.wikipedia.org/wiki/Body_area_network
2. A Comprehensive Survey of Wireless Body Area Networks
https://www.researchgate.net/publication/45709672_A_Comprehensive_Survey_of_Wireless_Body_Area_Networks
3. Wearable Wireless Body Area Networks for Medical Applications
https://onlinelibrary.wiley.com/doi/10.1155/2021/5574376
4.Moving Towards Body-to-Body Sensor Networks for Ubiquitous Applications: A Survey
https://www.mdpi.com/2224-2708/8/2/27
Resource Allocation in Wireless Body Area Networks: A Smart City Perspective
https://www.intechopen.com/chapters/80045
WIRELESS BODY AREA NETWORKS: A NEW PARADIGM OF PERSONAL SMART HEALTH.
https://smartcities.ieee.org/images/files/pdf/SCWhitePaper-WirelessBodyAreaNetworks.pdf
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1. Wireless Body Area Networks and Their Applications—A Review
https://ieeexplore.ieee.org/document/10024829 2.Prospect of Internet of Medical Things: A Review on Security Requirements and Solutions https://www.mdpi.com/1424-8220/22/15/5517 |
The exploitation of Smart applications for surveillance is not limited to hackers. Authorities, governments, and bad actors can also misuse these systems for surveillance beyond what is legally or ethically justified:
Government Overreach: There's a risk that state entities might use these technologies for mass surveillance, monitoring citizens' activities without due cause, potentially infringing on civil liberties.
Corporate Surveillance: Companies might leverage smart city data for profit, tracking consumer behavior in ways that might not be transparent or consensual.
Manipulation: In the wrong hands, surveillance data could be used to manipulate outcomes, suppress dissent, or target specific groups within society. This underlines the need for strong legal frameworks, transparent policies, and public oversight to ensure that the benefits of smart city technologies, including AI integration, do not come at the cost of privacy and freedom.
click link below
https://www.nestoropetaia.com/origins-and-the-global-surveillance-networks.html
In essence, if exploited the 4g and 5g smart city becomes a surveillance city where technologies can track movements and habits, opening up possibilities for privacy breaches and safety risks, thus becoming a free-for-all to hackers, authorities, governments and anyone with espionage, profiling, or control and manipulation agendas.
The vulnerabilities in each components of the smart enviroment is daunting, but what if the entire infrastructure can be controlled and manipulated holistically?
1. It probably already does work as a hive system.
2. It is completely possible because Militaries worldwide are using the same type of "net centric communications and applications"with A.I integration at the helm, which are advancing by the day via 6g, 7g, rollouts.
3. Yes. from first hand experience "everyday". Also from many targeted individual accounts, whether they are aware of it or not.
The vulnerabilities in each components of the smart enviroment is daunting, but what if the entire infrastructure can be controlled and manipulated holistically?
1. It probably already does work as a hive system.
2. It is completely possible because Militaries worldwide are using the same type of "net centric communications and applications"with A.I integration at the helm, which are advancing by the day via 6g, 7g, rollouts.
3. Yes. from first hand experience "everyday". Also from many targeted individual accounts, whether they are aware of it or not.