Smart City Model: a Literature Review

Achmad, Kusuma Adi; Nugroho, Lukito Edi; Djunaedi, Achmad; Widyawan,

doi:10.1109/iciteed.2018.8534865

Cited by 11 publications

(4 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The same issues have existed since people first started settling in cities more than 6000 years ago: sanitization, crime, traffic, tax collection, upkeep of public infrastructure, and emergency services (Albino et al, 2015) . Infrastructure is also necessary for the development of significant technological advancements, including the electric grid, telephone and cell phone networks, internet (including fiber optic and cable networks), hot and cold running water, water and waste treatment, garbage and recycling collection, public parks and recreation facilities, rail, light rail, and automotive streets, roads, thoroughfares, and rights-ofway (Achmad et al, 2018;. The main components of a smart city are presented in the Figure 1.…”

Section: Smart Cities and Waste Management 21 What Is Smart City?mentioning

confidence: 99%

Untitled

2023

SPSUTOM

View full text Add to dashboard Cite

Organizations nowadays are increasingly using a nondisclosure agreement to protect against the dissemination of certain information by employees. However, such methods have not always been successful, especially since a pandemic. Therefore, the aim of the article is to present the main trust factors. Identification of trust-building factors in the organization in order to increase efficiency and reduce indirect costs, as well as conduct theoretical analysis on this topic. Design/methodology/approach: The synthesis method and the analytical and comparative concept of building staff motivation were used. The theoretical analysis in the text is based on research that can be found in Polish, English and Russian literature. Findings:The article shows that by engaging the right disciplines it become possible to achieve absolute trust, which in turn serves as the key to effective work. Research limitations/implications: Building an atmosphere of trust begins with ways of learning, sharing information and knowledge while meeting the needs of the trusted person. Therefore, in future research on trust in the area of management, it is necessary to take into account the point of view of the related disciplines mentioned in the article. Social implications: A conscious desire to build organizational trust leads to an increase in work efficiency and a decrease in corrupt practices. Ultimately, this will lead to increased meaning of trust in business.Originality/value: A model of trust levels and their impact on work performance has been developed. The article can be used by the management as a guide to creating employee motivation systems.

show abstract

Section: Smart Cities and Waste Management 21 What Is Smart City?mentioning

confidence: 99%

Untitled

2023

SPSUTOM

View full text Add to dashboard Cite

show abstract

“…In particular, considering wider areas such as smart campuses, the employed IoT system must provide some LPWAN connectivity, which can deal with these demands [25][26][27][28][29][30]. Finally, in the context of smart cities, the goals can be more ambitious and reach more people, by aiming at sustainability, improving the life conditions of the population, and encouraging the creation of a creative economy [31][32][33].…”

Section: The Role Of Iot In Smart Environmentsmentioning

confidence: 99%

On the Use of LoRaWAN for the Monitoring and Control of Distributed Energy Resources in a Smart Campus

et al. 2020

View full text Add to dashboard Cite

The application of the most recent advances of the Internet-of-Things (IoT) technology to the automation of buildings is emerging as a promising solution to achieve greater efficiencies in energy consumption, and to allow the realization of sustainable models. The application of IoT has been demonstrated as effective in many fields, such as confirmed, for instance, by the Industry 4.0 concepts, which are revolutionizing modern production chains. By following this approach, the use of distributed control architectures and of IoT technologies (both wired and wireless) would result in effective solutions for the management of smart environments composed of groups of buildings, such as campuses. In this case, heterogeneous IoT solutions are typically adopted to satisfy the requirements of the very diverse possible scenarios (e.g., indoor versus outdoor coverage, mobile versus fixed nodes, just to mention a few), making their large-scale integration cumbersome. To cope with this issue, this paper presents an IoT architecture able to transparently manage different communication protocols in smart environments, and investigates its possible application for the monitoring and control of distributed energy resources in a smart campus. In particular, a use–case focused on the integration of the Long Range Wide Area Network (LoRaWAN) technology is considered to cope with heterogeneous indoor and outdoor communication scenarios. The feasibility analysis of the proposed solution is carried out by computing the scalability limits of the approach, based on the proposed smart campus data model. The results of the study showed that the proposed solution would be able to manage more than 10,000 nodes. An experimental validation of the LoRaWAN technology confirms its suitability in terms of coverage and latency, with a minimum LoRaWAN cell coverage range of 250 m, and a communication latency of about 400 ms. Finally, the advantages of the proposed solution in the supervision and management of a PV system are highlighted in a real-world scenario.

show abstract

“…The services are classified in some branches such as living, governance, economy, environment, education, healthcare, safety, security [21,22,23]. Those services can be ensured by using resources like brainware, hardware, and software [21]. To ensure the services by using the resources, a bunch of technological aspects should be considered with respect to quality features.…”

Section: Literature Reviewmentioning

confidence: 99%

IEF2C: A novel AI-powered framework for suspected COVID-19 patient detection and contact tracing in smart cities

Rahman

Mahmud

Rahman

2020

Preprint

View full text Add to dashboard Cite

Novel coronavirus disease 2019 (COVID-19) has found as a climacteric pandemic that spreads from human-to-human through contiguity. It is not possible to control the virus properly because its vaccine has not been discovered yet. As of now, various contact tracing approaches are being taken to contain the spread of the virus by breaking its transmission chain. Recently, few technologies are being exploited for contact tracing such as geological location, Bluetooth and google maps. Governments of some countries have already launched contact tracing applications to identify the close contact people of COVID-19 positive patients.However, these methods may not be effective without a huge amount of testing facility since the tracing action starts when a COVID-19 testing result is found positive. In this paper, we have proposed a novel AI-powered data management framework for smart city named IoT-to-Edge-to-Fog-to-cloudlet-to-Cloud (IEF2C) data management framework which will be exploited to identify the COVID-19 suspected patients in smart cities and also be used to inform the surrounding people about the suspected patient. The proposed framework is isolated into five layers which have different tasks such as data collection, processing, authentication and storage. The framework will bring all the citizens under a common platform as well as will ensure the user and device mobility. It will mitigate the information gap by helping concerned authorities and users to take proper steps in such a pandemic era.

show abstract

Smart City Model: a Literature Review

Cited by 11 publications

References 15 publications

Untitled

Untitled

On the Use of LoRaWAN for the Monitoring and Control of Distributed Energy Resources in a Smart Campus

IEF2C: A novel AI-powered framework for suspected COVID-19 patient detection and contact tracing in smart cities

Contact Info

Product

Resources

About