A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> D. Internet of Things <s> Microlocation is the process of locating any entity with a very high accuracy (possibly in centimeters), whereas geofencing is the process of creating a virtual fence around a point of interest (PoI). In this paper, we present an insight into various microlocation enabling technologies, techniques, and services. We also discuss how they can accelerate the incorporation of Internet of Things (IoT) in smart buildings. We argue that micro-location-based location aware solutions can play a significant role in facilitating the tenants of an IoT-equipped smart building. Also, such advanced technologies will enable the smart building control system through minimal actions performed by the tenants. We also highlight the existing and envisioned services to be provided by using microlocation enabling technologies. We describe the challenges and propose some potential solutions, such that microlocation enabling technologies and services are thoroughly integrated with IoT-equipped smart building. <s> BIB001 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> D. Internet of Things <s> With the increasing demand of smart objects in our everyday life promotes an advance generation of communications under the umbrella of the Internet of Things (IoT). For IoT, location-based service is one of the main service, while localization accuracy is a primary problem. Rather than linearizing the nonlinear cost function, we propose a novel subspace algorithm by using the time of arrival (TOA) measurements. Our propose algorithm provide closed-form solution and is validated to be robust even for large measurement noise, as the dimension awareness and eigenstructure of scalar product matrix is used. We evaluate the proposed algorithm by comparing with Cramer-Rao Lower Bound (CRLB) and show its performance through simulation experiments using MATLAB. <s> BIB002 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> D. Internet of Things <s> The demand of smart objects in our life promotes an advanced generation of communications under the umbrella of Internet of Things (IoT). In IoT, location-based service is one of the most promising services, where localization accuracy is a crucial problem. Rather than linearizing a nonlinear cost function used in ordinary localization problem, we propose a novel subspace algorithm by using the time of arrival (TOA) measurements. Our algorithm provides a closed-form solution and is validated to be robust for large measurement noise, as the dimension awareness and eigen structure of scalar product matrix are used. Moreover, we develop a Cramer-Rao Lower Bound (CLB) for 3-dimensional (3D) localization by using the TOA measurements. We evaluate the proposed algorithm by comparing with CLB and show its performance through simulation experiments. <s> BIB003
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 BIB001 . MDS based localization methods can be of great use in smart systems such as smart bulidings, smart grids, and smart cities. MDS based localization for IoT networks is still an open research area where very few work exists BIB002 , BIB003 ,  .