# Survey of Localization for Internet of Things Nodes: Approaches, Challenges and Open Issues
## 1 Introduction  
The Internet of Things (IoT) allows the connections of a large number of sensors, actuators, and smart devices for persisting connectivity. Localization is an essential process in the IoT environment for tracking and monitoring the targets with the help of sensor nodes. The sensor nodes collect the target information and transfer it to the central controller for further processing. These applications demand information about the position of the sensor node, which is also essential in routing and clustering. The location of a node is generally determined by using geometric measures like triangulation and trilateration. The distance between any two nodes is determined using radio signal strength, coordination, important features of the resonant waves, and others. Localization approaches in wireless sensor nodes are independent of earlier location specifications; they rely on the location information of some particular sensor nodes and the internetwork measures [1]. The sensor nodes providing prior location information are known as anchor or reference nodes whose location is determined by the global positioning system (GPS). Recently, researchers have started studying localization in IoT networks for numerous applications [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]. However, all the sensor nodes cannot be equipped with GPS due to the cost, energy efficiency andGPS signal unavailability in certain environments. Consequently, different approaches based on using a minimum number of anchor nodes to locate the other sensor nodes by information exchange among sensor and anchor nodes are proposed in the literature [2].  
Node localization algorithms are mainly categorized as range-based localization and range-free localization. The range-based method utilizes hop distances, hop counts and angles for a position estimate. In contrast, the range-free method is based on the connectivity or pattern mapping for location approximation. Hybrid localization approaches developed by combining various range-based methods are precise and provide improved coverage [3]. Range-based schemes are partitioned into four categories by considering deployment scenarios; stationary sensor and stationary anchor nodes, stationary sensor and moving anchor nodes moving sensor and stationary anchor nodes, moving sensor and moving anchor nodes [4; 5; 6]. Device-based and device-free technologies are used for the localization of IoT nodes. Device-based technologies have progressed exceptionally towards the optimal location approximation, whereas device-free technologies are well suited for various application scenarios. Although various localization techniques are available for solving position estimate problems in the IoT networks, there are practical limitations in combining these techniques and deploying the minimum number of anchor nodes in such setups. Therefore, it is essential to design cost-effective and appropriate localization schemes. The motivation behind this review is in the study of distinct localization techniques and their applications in IoT environments.  
In this paper, we present an in-depth review of range-free and range-based localization techniques and related concepts. The rest of the paper is organized as follows. Section 2 focuses on the classification of localization approaches. Section 3 presents the measurement techniques used for localization, covering the range-based and range-free techniques and their subtypes. Section 4 discusses device-based and device-free localization methods. We also discuss the crucial problems and fundamental challenges, and technologies. In Section 5, important smart applications such as smart city, health and industry, where localization plays a crucial role, are presented. Section 6 illustrates and compares the various metrics used in the performance evaluation of localization techniques. The paper is concluded in Section 7.