PrecaElevator: Towards Zero-Waiting Time on Calling Elevator By Utilizing Context Aware Platform in Smart Building

Ge, Hangli; Hamada, Takeo; Sumitomo, Takahiro; Koshizuka, Noboru

doi:10.1109/gcce.2018.8574706

Cited by 7 publications

(3 citation statements)

References 5 publications

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“…They used context-based reasoning models for defining transition rules and triggering to reduce the energy consumption on a university campus. Another study [17] described a proposal for creating an elevator system in smart buildings capable of reducing the passenger waiting time by preregistering elevator calls using context information. This system captures the context data of the location of the passenger and, based on a 3D localization model, makes automatic preregistration to the elevator considering the distance between the passenger and the elevator.…”

Section: Implementations Of Context-aware Systems To Iot-based Smart Environmentsmentioning

confidence: 99%

Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation

Muñoz-Arcentales

López-Pernas

Conde

et al. 2021

Sensors

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In recent years, many proposals of context-aware systems applied to IoT-based smart environments have been presented in the literature. Most previous works provide a generic high-level structure of how a context-aware system can be operationalized, but do not offer clues on how to implement it. On the other hand, there are many implementations of context-aware systems applied to specific IoT-based smart environments that are context-specific: it is not clear how they can be extended to other use cases. In this article, we aim to provide an open-source reference implementation for providing context-aware data analytics capabilities to IoT-based smart environments. We rely on the building blocks of the FIWARE ecosystem and the NGSI data standard, providing an agnostic end-to-end solution that considers the complete data lifecycle, covering from data acquisition and modeling, to data reasoning and dissemination. In other words, our reference implementation can be readily operationalized in any IoT-based smart environment regardless of its field of application, providing a context-aware solution that is not context-specific. Furthermore, we provide two example use cases that showcase how our reference implementation can be used in a variety of fields.

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Section: Implementations Of Context-aware Systems To Iot-based Smart Environmentsmentioning

confidence: 99%

Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation

Muñoz-Arcentales

López-Pernas

Conde

et al. 2021

Sensors

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show abstract

“…If potential passenger was detected in the places, then a reservation call would be automatically generated on the elevator for reducing the passengers' waiting time. Hangli et al presented an approach that enabled passengers to register the elevator landing-call remotely based on the location-aware platform in smart building for reducing the passengers' waiting time [21]. Suzuki et al proposed that the optimally assigned elevator cabin number could be presented at the ID-card authorized gate for optimizing passengers' waiting time of elevator [24].…”

Section: Related Workmentioning

confidence: 99%

Intellevator: An Intelligent Elevator System Proactive in Traffic Control for Time-Efficiency Improvement

Hamada

Sumitomo

et al. 2020

IEEE Access

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Elevator functioning as a vertical transport facility remains stand-alone and incapable of accessing the fine-grained traffic information. It significantly restricts the flexibility and efficiency of vertical transporting. In particular, while in peak-time, the limited elevator physical capacity with the momentary traffic increment gives rise to the vertical traffic bottleneck problem in large-scale buildings. The problem further results in the long waiting, dissatisfaction, frustration of passengers. In this paper, we present our proposal named Intellevator: an intelligent elevator system that enables the passively functioning elevator system be proactive and intelligent in traffic control for optimizing the transport efficiency. The proposal is an end-to-end architecture that composed of three aspects: Internet of things (IoT)-enabling technology on a conventional elevator; an agent server to enhance elevator computational capability and a novel user interface for delivering system intelligence to end-users. The proposal was experimented on a conventional elevator in a built smart-building environment. Numerical simulation results have demonstrated the system efficiency improvement. In addition, the system usability and user experience have been evaluated by a user study as well.

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“…An example for a context-aware application is a context-aware tour guide, which provides information to their users depending on their location and/or personal preference [3]. Another example is the pre-registration of elevators in a smart building using the localization of passengers within the callable range of an elevator, which should reduce the waiting time for passengers [4]. Numerous such examples can be found in different application areas, such as health care [5], residences for the elderly [6] and industrial applications [7].…”

Section: Introductionmentioning

confidence: 99%

Building a COVID-Safe Navigation App Using a Meta-Model Based Context Server

Wojciechowski

Pogscheba

2022

Sensors

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Building context-aware applications is an already widely researched topic. It is our belief that context awareness has the potential to supplement the Internet of Things, when a suitable methodology including supporting tools will ease the development of context-aware applications. We believe that a meta-model based approach can be key to achieving this goal. In this paper, we present our meta-model based methodology, which allows us to define and build application-specific context models and the integration of sensor data without any programming. We describe how that methodology is applied with the implementation of a relatively simple context-aware COVID-safe navigation app. The outcome showed that programmers with no experience in context-awareness were able to understand the concepts easily and were able to effectively use it after receiving a short training. Therefore, context-awareness is able to be implemented within a short amount of time. We conclude that this can also be the case for the development of other context-aware applications, which have the same context-awareness characteristics. We have also identified further optimization potential, which we will discuss at the conclusion of this article.

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PrecaElevator: Towards Zero-Waiting Time on Calling Elevator By Utilizing Context Aware Platform in Smart Building

Cited by 7 publications

References 5 publications

Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation

Enabling Context-Aware Data Analytics in Smart Environments: An Open Source Reference Implementation

Intellevator: An Intelligent Elevator System Proactive in Traffic Control for Time-Efficiency Improvement

Building a COVID-Safe Navigation App Using a Meta-Model Based Context Server

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