Synergy of IoT and AI in Modern Society: The Robotics and Automation Case

Tzafestas, Spyros G.

doi:10.19080/raej.2018.03.555621

Cited by 25 publications

(10 citation statements)

References 2 publications

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“…Unlike the safe city, which has an almost universal definition, the smart city has numerous definitions but most of them converge at the point of interlinkage of city fabrics through the help of technology through the bias of 'smart' components and 'smart' systems. Amongst the advanced technologies that are employed in the management of urban centres is that of IoT, whose protocols and infrastructure have greatly benefited the concept of smart cities [18,20,53,54]. The availability and advancement of IoT technology has allowed the development of a wide variety of smart devices, sensors, social networks and systems [55,56].…”

Section: The Smart Citymentioning

confidence: 99%

The Emergence of Anti-Privacy and Control at the Nexus between the Concepts of Safe City and Smart City

Allam

2019

Smart Cities

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The emergence of Big Data, accelerated through the Internet of Things (IoT) and Artificial Intelligence, from the emerging, contemporary concept of smart cities coupled with that of the notion for safe cities is raising concerns of privacy and good governance that are impacting on socio-economic and liveability dimensions of urban fabrics. As these gain ground, largely due to economic pressures from large ICT providers, there is a notable increase towards the need for inclusion of human dimensions, complemented by the use of technology. However, the latter is seen as catalysing elements of control and propaganda which are thriving through oversimplified and non-inclusive urban IT policy measures. This paper dwells on the intersecting subjects of smart and safe cities and explores the highlighted issues that are deemed to cause concern and further explore the need for transparency and inclusivity in urban processes and systems. This paper is oriented towards urban planners and policy makers looking at the implementation of smart and safe cities concepts.

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Section: The Smart Citymentioning

confidence: 99%

The Emergence of Anti-Privacy and Control at the Nexus between the Concepts of Safe City and Smart City

Allam

2019

Smart Cities

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“…Data from these sensors revolutionized areas such as health, security, governance, transport, and energy sectors, amongst many others. Through data from IoT-enabled components, the use of artificial intelligence for data processing saw a rise in different environments such as business, healthcare, research and development, the financial sector, manufacturing, weather, social circles, and more [65,66].…”

Section: Emerging Network In Smart Citiesmentioning

confidence: 99%

“…A combination of the three technologies has the potential to allow for intricate exercises such as analysis and prediction of human behavior using smart devices, for example, motion sensors and facial recognition devices [69]. These technologies also allow for smart data storage and retrieval of data and information, as well as the automation of tasks and activities in places like traffic control, street lighting, and light and temperature control in buildings, amongst others [66,70]. In the business world, Naganathan and Rao [71] explained that using these technologies will increase efficiency and productivity and provide an unprecedented competitive advantage.…”

Section: Emerging Network In Smart Citiesmentioning

confidence: 99%

Achieving Neuroplasticity in Artificial Neural Networks through Smart Cities

Allam

2019

Smart Cities

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Through the Internet of things (IoT), as promoted by smart cities, there is an emergence of big data accentuating the use of artificial intelligence through various components of urban planning, management, and design. One such system is that of artificial neural networks (ANNs), a component of machine learning that boasts similitude with brain neurological networks and its functioning. However, the development of ANN was done in singular fashion, whereby processes are rendered in sequence in a unidimensional perspective, contrasting with the functions of the brain to which ANN boasts similitude, and in particular to the concept of neuroplasticity which encourages unique complex interactions in self-learning fashion, thereby encouraging more inclusive urban processes and render urban coherence. This paper takes inspiration from Christopher Alexander’s Nature of Order and dwells in the concept of complexity theory; it also proposes a theoretical model of how ANN can be rendered with the same plastic properties as brain neurological networks with multidimensional interactivity in the context of smart cities through the use of big data and its emerging complex networks. By doing so, this model caters to the creation of stronger, richer, and more complex patterns that support Alexander’s concept of “wholeness” through the connection of overlapping networks. This paper is aimed toward engineers with interdisciplinary interest looking at creating more complex and intricate ANN models, and toward urban planners and urban theorists working on the emerging contemporary concept of smart cities.

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“…Ai is generally distinguished into two types as narrow AI and general AI. The narrow AI includes intelligent systems that are able to perform certain tasks without being programmed specifically while the general AI is a form of intelligence technique that is able to learn the methods needed for performing the assigned tasks [4]. Some of the QoS parameters studied in this paper are end-to-end delay, throughput, packet delivery ratio, and jitter and energy consumption.…”

Section: Introductionmentioning

confidence: 99%

Improvement of QoS Parameters of IoT Networks Using Artificial Intelligence

Sheikh

Kumar

Ambhaikar

2021

Smart Innovation, Systems and Technologies

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The quality of service (QoS) parameters of IoT networks plays an important role in knowing the efficiency of an application. As the number of IoT users and devices is increasing and the number is envisaged to grow fast in the future, it has become extremely important to pay attention toward the QoS parameters for increasing the acceptability of the technology among the people. The IoT networks should be capable of handling devices of diverse nature and at the same time should provide wireless access to all of them. Artificial intelligence (AI) is one of the techniques to improve the QoS and has been used in this paper to know the change in the QoS parameters for networks with a varying number of nodes. The parameters studied in this paper are end-to-end delay, throughput, packet delivery ratio, and jitter and energy consumption. All the values have been calculated for a network with 30, 40, 50, 60, 70, 80, and 90 nodes. A comparison of QoS parameters by using AI and without AI has been explained. The results indicate that most of the parameters showed improvement in the values for all the sizes of network with the application of AI.

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Synergy of IoT and AI in Modern Society: The Robotics and Automation Case

Cited by 25 publications

References 2 publications

The Emergence of Anti-Privacy and Control at the Nexus between the Concepts of Safe City and Smart City

The Emergence of Anti-Privacy and Control at the Nexus between the Concepts of Safe City and Smart City

Achieving Neuroplasticity in Artificial Neural Networks through Smart Cities

Improvement of QoS Parameters of IoT Networks Using Artificial Intelligence

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