Improving consumer satisfaction in smart cities using edge computing and caching: A case study of date fruits classification

2018 ◽  
Vol 88 ◽  
pp. 333-341 ◽  
Author(s):  
M. Shamim Hossain ◽  
Ghulam Muhammad ◽  
Syed Umar Amin
2018 ◽  
pp. 60-67
Author(s):  
Henrika Pihlajaniemi ◽  
Anna Luusua ◽  
Eveliina Juntunen

This paper presents the evaluation of usersХ experiences in three intelligent lighting pilots in Finland. Two of the case studies are related to the use of intelligent lighting in different kinds of traffic areas, having emphasis on aspects of visibility, traffic and movement safety, and sense of security. The last case study presents a more complex view to the experience of intelligent lighting in smart city contexts. The evaluation methods, tailored to each pilot context, include questionnaires, an urban dashboard, in-situ interviews and observations, evaluation probes, and system data analyses. The applicability of the selected and tested methods is discussed reflecting the process and achieved results.


Author(s):  
Karan Bajaj ◽  
Bhisham Sharma ◽  
Raman Singh

AbstractThe Internet of Things (IoT) applications and services are increasingly becoming a part of daily life; from smart homes to smart cities, industry, agriculture, it is penetrating practically in every domain. Data collected over the IoT applications, mostly through the sensors connected over the devices, and with the increasing demand, it is not possible to process all the data on the devices itself. The data collected by the device sensors are in vast amount and require high-speed computation and processing, which demand advanced resources. Various applications and services that are crucial require meeting multiple performance parameters like time-sensitivity and energy efficiency, computation offloading framework comes into play to meet these performance parameters and extreme computation requirements. Computation or data offloading tasks to nearby devices or the fog or cloud structure can aid in achieving the resource requirements of IoT applications. In this paper, the role of context or situation to perform the offloading is studied and drawn to a conclusion, that to meet the performance requirements of IoT enabled services, context-based offloading can play a crucial role. Some of the existing frameworks EMCO, MobiCOP-IoT, Autonomic Management Framework, CSOS, Fog Computing Framework, based on their novelty and optimum performance are taken for implementation analysis and compared with the MAUI, AnyRun Computing (ARC), AutoScaler, Edge computing and Context-Sensitive Model for Offloading System (CoSMOS) frameworks. Based on the study of drawn results and limitations of the existing frameworks, future directions under offloading scenarios are discussed.


Buildings ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 78
Author(s):  
Daria Uspenskaia ◽  
Karl Specht ◽  
Hendrik Kondziella ◽  
Thomas Bruckner

Without decarbonizing cities energy and climate objectives cannot be achieved as cities account for approximately two thirds of energy consumption and emissions. This goal of decarbonizing cities has to be facilitated by promoting net-zero/positive energy buildings and districts and replicating them, driving cities towards sustainability goals. Many projects in smart cities demonstrate novel and groundbreaking low-carbon solutions in demonstration and lighthouse projects. However, as the historical, geographic, political, social and economic context of urban areas vary greatly, it is not always easy to repeat the solution in another city or even district. It is therefore important to look for the opportunities to scale up or repeat successful pilots. The purpose of this paper is to explore common trends in technologies and replication strategies for positive energy buildings or districts in smart city projects, based on the practical experience from a case study in Leipzig—one of the lighthouse cities in the project SPARCS. One of the key findings the paper has proven is the necessity of a profound replication modelling to deepen the understanding of upscaling processes. Three models analyzed in this article are able to provide a multidimensional representation of the solution to be replicated.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Martin Lnenicka ◽  
Stuti Saxena

Purpose The purpose of this paper is to study the select Smart Cities of Czech and Indian counterparts and assess the extent to which open government data (OGD) standards are being adhered to using select indicators. Design/methodology/approach This study integrates the benchmarking frameworks provided in literature on OGD and apply them to evaluate the OGD standards of the Smart Cities’ websites. Findings Whereas the Czech Smart Cities are relatively more advanced in their OGD initiatives, the Indian counterpart is far lagging behind in their endeavors. Originality/value While there are many studies on OGD and Smart Cities, there has been no study which seeks to appreciate if the OGD initiatives are being adhered to by the Smart Cities.


i-com ◽  
2021 ◽  
Vol 20 (2) ◽  
pp. 177-193
Author(s):  
Daniel Wessel ◽  
Julien Holtz ◽  
Florian König

Abstract Smart cities have a huge potential to increase the everyday efficiency of cities, but also to increase preparation and resilience in case of natural disasters. Especially for disasters which are somewhat predicable like floods, sensor data can be used to provide citizens with up-to-date, personalized and location-specific information (street or even house level resolution). This information allows citizens to better prepare to avert water damage to their property, reduce the needed government support, and — by connecting citizens locally — improve mutual support among neighbors. But how can a smart city application be designed that is both usable and able to function during disaster conditions? Which smart city information can be used? How can the likelihood of mutual, local support be increased? In this practice report, we present the human-centered development process of an app to use Smart City data to better prepare citizens for floods and improve their mutual support during disasters as a case study to answer these questions.


2021 ◽  
Vol 20 (5s) ◽  
pp. 1-22
Author(s):  
Haoran Li ◽  
Chenyang Lu ◽  
Christopher D. Gill

Fault-tolerant coordination services have been widely used in distributed applications in cloud environments. Recent years have witnessed the emergence of time-sensitive applications deployed in edge computing environments, which introduces both challenges and opportunities for coordination services. On one hand, coordination services must recover from failures in a timely manner. On the other hand, edge computing employs local networked platforms that can be exploited to achieve timely recovery. In this work, we first identify the limitations of the leader election and recovery protocols underlying Apache ZooKeeper, the prevailing open-source coordination service. To reduce recovery latency from leader failures, we then design RT-Zookeeper with a set of novel features including a fast-convergence election protocol, a quorum channel notification mechanism, and a distributed epoch persistence protocol. We have implemented RT-Zookeeper based on ZooKeeper version 3.5.8. Empirical evaluation shows that RT-ZooKeeper achieves 91% reduction in maximum recovery latency in comparison to ZooKeeper. Furthermore, a case study demonstrates that fast failure recovery in RT-ZooKeeper can benefit a common messaging service like Kafka in terms of message latency.


Information ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 270 ◽  
Author(s):  
Anne Faber ◽  
Sven-Volker Rehm ◽  
Adrian Hernandez-Mendez ◽  
Florian Matthes

Smart mobility is a central issue in the recent discourse about urban development policy towards smart cities. The design of innovative and sustainable mobility infrastructures as well as public policies require cooperation and innovations between various stakeholders—businesses as well as policy makers—of the business ecosystems that emerge around smart city initiatives. This poses a challenge for deploying instruments and approaches for the proactive management of such business ecosystems. In this article, we report on findings from a smart city initiative we have used as a case study to inform the development, implementation, and prototypical deployment of a visual analytic system (VAS). As results of our design science research we present an agile framework to collaboratively collect, aggregate and map data about the ecosystem. The VAS and the agile framework are intended to inform and stimulate knowledge flows between ecosystem stakeholders in order to reflect on viable business and policy strategies. Agile processes and roles to collaboratively manage and adapt business ecosystem models and visualizations are defined. We further introduce basic categories for identifying, assessing and selecting Internet data sources that provide the data for ecosystem models and we detail the ecosystem data and view models developed in our case study. Our model represents a first explication of categories for visualizing business ecosystem models in a smart city mobility context.


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