Microlocation for Internet-of-Things-Equipped Smart Buildings

Zafari, Faheem; Papapanagiotou, Ioannis; Christidis, Konstantinos

doi:10.1109/jiot.2015.2442956

Cited by 182 publications

(78 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Localization can be of great benefit to IoT networks, for instance, automated services such as handling devices in an office based on users' location. IoT requires the accuracy of localization in centimeters, therefore, the term used for locating an entity in IoT network is called microlocation [240]. MDS based localization methods can be of great use in smart systems such as smart bulidings, smart grids, and smart cities.…”

Section: Internet Of Thingsmentioning

confidence: 99%

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

Saeed

Nam

Al-Naffouri

et al. 2019

IEEE Commun. Surv. Tutorials

135

View full text Add to dashboard Cite

Current and future wireless applications strongly rely on precise real-time localization. A number of applications such as smart cities, Internet of Things (IoT), medical services, automotive industry, underwater exploration, public safety, and military systems require reliable and accurate localization techniques. Generally, the most popular localization/ positioning system is the Global Positioning System (GPS). GPS works well for outdoor environments but fails in indoor and harsh environments. Therefore, a number of other wireless local localization techniques are developed based on terrestrial wireless networks, wireless sensor networks (WSNs) and wireless local area networks (WLANs). Also, there exist localization techniques which fuse two or more technologies to find out the location of the user, also called signal of opportunity based localization. Most of the localization techniques require ranging measurements such as time of arrival (ToA), time difference of arrival (TDoA), direction of arrival (DoA) and received signal strength (RSS). There are also range-free localization techniques which consider the proximity information and do not require the actual ranging measurements. Dimensionality reduction techniques are famous among the range free localization schemes. Multidimensional scaling (MDS) is one of the dimensionality reduction technique which has been used extensively in the recent past for wireless networks localization. In this paper, a comprehensive survey is presented for MDS and MDS based localization techniques in WSNs, Internet of Things (IoT), cognitive radio networks, and 5G networks. 2 MDS is much popular among all these techniques because of its simplicity and many application areas. MDS analysis finds the spatial map for objects given that the similarity or dissimilarity information between the objects is available [16].In the recent past, MDS is widely used for localization and mapping of wireless sensor networks (WSNs) and the internet of things (IoT). In [17] a proximity information based sensor network localization is proposed, where the main idea is to construct a local configuration of sensor nodes by using classical MDS (CMDS). The MDS based localization algorithms in [17] and [18] are centralized with higher computational complexity [7]. Semi-centralized (or clustered) MDS techniques are developed to compute local coordinates of nodes, which then are refined to find the final position of the nodes [19], [20]. In [21], [22] and [23] the authors proposed manifold learning to estimate the sensor nodes position in wireless sensor networks. In [24] the authors proposed Nystrom approximation for the proximity information matrix in MDS to reduce its size for better localization accuracy in sensor networks. Distributed MDS based localization algorithm is proposed in [25] with noisy range measurements, where the authors assume that the distances are corrupted with independent Gaussian random noise. MDS methods with different refinement schemes have also been proposed in the literature t...

show abstract

Section: Internet Of Thingsmentioning

confidence: 99%

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

Saeed

Nam

Al-Naffouri

et al. 2019

IEEE Commun. Surv. Tutorials

135

View full text Add to dashboard Cite

show abstract

“…However, it is vital to have a good understanding of the main standard bodies and companies involved in shaping the development of SBs [1]. The Institute for Building Efficiency [24] focuses on the operation of buildings to provide efficient healthy and comfortable environment [25]. IBM [26] focuses also on the operation of SBs to provide integrated physical and digital infrastructures that provide reliable, sustainable, and costeffective occupancy services.…”

Section: Smart Buildings: Concept and Architecturementioning

confidence: 99%

Leveraging Machine Learning and Big Data for Smart Buildings: A Comprehensive Survey

et al. 2019

View full text Add to dashboard Cite

Future buildings will offer new convenience, comfort, and efficiency possibilities to their residents. Changes will occur to the way people live as technology involves into people's lives and information processing is fully integrated into their daily living activities and objects. The future expectation of smart buildings includes making the residents' experience as easy and comfortable as possible. The massive streaming data generated and captured by smart building appliances and devices contains valuable information that needs to be mined to facilitate timely actions and better decision making. Machine learning and big data analytics will undoubtedly play a critical role to enable the delivery of such smart services. In this paper, we survey the area of smart building with a special focus on the role of techniques from machine learning and big data analytics. This survey also reviews the current trends and challenges faced in the development of smart building services.

show abstract

“…the process of locating moving objects in micro spaces such as buildings) together with IoT architecture implementations will facilitate several processes in Smart Buildings. Zafari et al (2016) explained that microlocation is the process of locating any entity with a very high accuracy (possibly in centimetres), whereas geofencing is the process of creating a virtual fence around a point of interest (PoI). The authors argued that microlocation-based location aware solutions will enable the smart building control system through minimal actions performed by the tenants.…”

Section: Buildings Integrated Into Business Processesmentioning

confidence: 99%

Integration of Geo-Sensor Feeds and Event Consumer Services for Real-Time Representation of Iot Nodes

Işıkdağ¹,

Pilouk²

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:More and more devices are starting to be connected to the Internet every day. Internet-of-Things (IoT) is known as an architecture where online devices have the ability to communicate and interact with each other in real-time. On the other hand, with the development of IoT related technologies information about devices (i.e. Things) can be acquired in real-time by the humans. The implementation of IoT related technologies requires new approaches to be investigated for novel system architectures. These architectures need to have 3 main abilities. The first one is the ability is to store and query information coming from millions of devices in real-time. The second one is the ability to interact with large number of devices seamlessly regardless of their hardware and their software platforms. The final one is the ability to visualise and present information coming from millions of sensors in real time. The paper provides an architectural approach and implementation tests for storage, exposition and presentation of large amounts of real-time geo-information coming from multiple IoT nodes (and sensors).

show abstract

Microlocation for Internet-of-Things-Equipped Smart Buildings

Cited by 182 publications

References 57 publications

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques

Leveraging Machine Learning and Big Data for Smart Buildings: A Comprehensive Survey

Integration of Geo-Sensor Feeds and Event Consumer Services for Real-Time Representation of Iot Nodes

Contact Info

Product

Resources

About