Efficient Rule Engine for Smart Building Systems

Sun, Yan; Wu, Tin-Yu; Zhao, Guotao; Guizani, Mohsen

doi:10.1109/tc.2014.2345385

Cited by 45 publications

(21 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An obvious pain point is the inability of existing middleware to internalize an expressive and complete notion of context, a need that has been identified in both the research community [36] and in the industry [9]. Existing work incorporating context-awareness into IoT-like applications adopts a semantic approach [17], [24], [38], [39], where context-awareness relies on a pre-defined ontology characterizing devices, users, and their relationships. In contrast, providing users seamless experiences requires an approach that does not rely on a user having a priori knowledge about how IoT devices affect the space in which they are located.…”

Section: Motivation and Related Workmentioning

confidence: 99%

rIoT: Enabling Seamless Context-Aware Automation in the Internet of Things

Hua

Liu

Kalbarczyk

et al. 2019

2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)

View full text Add to dashboard Cite

Advances in mobile computing capabilities and an increasing number of Internet of Things (IoT) devices have enriched the possibilities of the IoT but have also increased the cognitive load required of IoT users. Existing context-aware systems provide various levels of automation in the IoT. Many of these systems adaptively take decisions on how to provide services based on assumptions made a priori. The approaches are difficult to personalize to an individual's dynamic environment, and thus today's smart IoT spaces often demand complex and specialized interactions with the user in order to provide tailored services. We propose rIoT, a framework for seamless and personalized automation of human-device interaction in the IoT. rIoT leverages existing technologies to operate across heterogeneous devices and networks to provide a one-stop solution for device interaction in the IoT. We show how rIoT exploits similarities between contexts and employs a decision-tree like method to adaptively capture a user's preferences from a small number of interactions with the IoT space. We measure the performance of rIoT on two realworld data sets and a real mobile device in terms of accuracy, learning speed, and latency in comparison to two state-of-the-art machine learning algorithms.

show abstract

Section: Motivation and Related Workmentioning

confidence: 99%

rIoT: Enabling Seamless Context-Aware Automation in the Internet of Things

Hua

Liu

Kalbarczyk

et al. 2019

2019 IEEE 16th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)

View full text Add to dashboard Cite

show abstract

“…With user-specified requests, the data which are not included could be filtered out at an early state. This could be accomplished by many approaches, for instance, rule-based engine in [11], query-based acquisitional system in [16], and publish-subscribe procedure in [12,13].…”

Section: Application Level Data Reduction and Quality Controlmentioning

confidence: 99%

“…Along with reducing amount, the quality of service (QoS) such as throughputs and delays could also be specified and controlled [10]. Above the service level, the solutions on application level exploit userspecified requirements to draw only requested data streams (i.e., drop unrequested streams) [11][12][13]. For example, in a lighting control system of smart buildings, the data from movement and occupancy sensors are significant while data from temperature and heat detectors are ignorable.…”

Section: Introductionmentioning

confidence: 99%

Two-Tier VoI Prioritization System on Requirement-Based Data Streaming toward IoT

Choochotkaew¹,

Yamaguchi²,

Higashino³

2017

Mobile Information Systems

View full text Add to dashboard Cite

Toward the world of Internet of Things, people utilize knowledge from sensor streams in various kinds of smart applications. The number of sensing devices is rapidly increasing along with the amount of sensing data. Consequently, a bottleneck problem at the local gateway has attracted high concern. An example scenario is smart elderly houses in rural areas where each house installs thousands of sensors and all connect to resource-limited and unstable 2G/3G networks. The bottleneck state can incur unacceptable latency and loss of significant data due to the limited waiting-queue. Orthogonally to the existing solutions, we propose a two-tier prioritization system to enhance information quality, indicated by VoI, at the local gateway. The proposed system has been designed to support several requirements with several conflicting criteria over shared sensing streams. Our approach adopts Multicriteria Decision Analysis technique to merge requirements and to assess the VoI. We introduce the framework that can reduce the computational cost by precalculation. Through a case study of building management systems, we have shown that our merge algorithm can provide 0.995 cosine-similarity for representing all user requirements and the evaluation approach can obtain satisfaction values around 3 times higher than the naïve strategies for the top-list data.

show abstract

“…schools, museums, subway stations and tunnels. As a result, we shall improve the level of comfort and productivity of the people in their modern life (Wei et al, 2012;Ghayvat et al, 2015;Kelesetal, 2015;Bellagente et al, 2015;Tao et al, 2016;Sun et al, 2015;Wang et al, 2016;Magno et al, 2015). Traditionally, the above urban IoT infrastructure is capable of integrating different technologies within the current Internet infrastructure to transmit the IoT data (Corna et al, 2015;Kausar et al, 2012;Kim et al, 2010;Yang et al, 2010;Li and Yu, 2011;Xu et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

An Open Source Data Visualization System for Wireless Sensor Network

Wei¹,

Lu²,

Zhang³

2017

JCSIT

View full text Add to dashboard Cite

This paper presents a data visualization scheme for wireless sensor network which plays an important role in the structure of Internet of Things (IoT). In the infrastructure of IoT, data collected by its end nodes with different sensors can be used to monitor the energy consumption and the salubrity of the environment in public buildings in order to further improve the level of comfort and productivity of the people in these environments. However, the data collected by the wireless sensors at the end nodes of IoT cannot always be directly connected to Internet and provide web-based service to users for some special situations, e.g. electric transport towers installed at remote mountains. In this paper, we propose a framework that uses both open source hardware and software to collect the data at the end nodes from a wireless sensor network while visualizing the data without network gateway and/or web-based cloud server. A Zig Bee based wireless sensor network was applied to achieve an efficient and economical solution to monitor the device in real time and transmit these data to IoT. Experiment results demonstrated that the proposed framework is feasible for achieving an efficient and low-cost visualization system in the wireless sensor network.

show abstract

Efficient Rule Engine for Smart Building Systems

Cited by 45 publications

References 17 publications

rIoT: Enabling Seamless Context-Aware Automation in the Internet of Things

rIoT: Enabling Seamless Context-Aware Automation in the Internet of Things

Two-Tier VoI Prioritization System on Requirement-Based Data Streaming toward IoT

An Open Source Data Visualization System for Wireless Sensor Network

Contact Info

Product

Resources

About