# A Review of Pedestrian Indoor Positioning Systems for Mass Market Applications
## 1 Introduction  
The estimation of the position of a target in an outdoor environment is usually solved employing Global Navigation Satellite Systems (GNSS). Notwithstanding, in the case of indoor environments there is an absence of a standard positioning system that can be worldwide applied. For this reason, the research efforts of authors working in the field of positioning have been recently focused in indoor scenarios. Indoor Positioning Systems (IPS) have been designed for providing information about the position of a person or object inside a building. In fact, the evolution of IPS facilitates the creation of Indoor Location Based Services (ILBS) which build applications on top of the knowledge of the position. Examples of these kinds of services are the location of products stored in a warehouse, the tracking of equipment inside a hospital, the guidance of firemen inside buildings with reduced visibility due to smoke, among others like the guidance of people inside airports or the development of assisted living systems for elderly care. Indeed, the predicted market value of indoor location services for 2020 is USD 10 billion [1]. Therefore, there is a special interest in developing IPS that can be easily scaled to mass market applications and deployed in millions of buildings in the world. There are three main requirements for an IPS that aims to be applied to mass market applications: (i) the system must provide accurate position estimations; (ii) the system must be easily scalable; and (iii) the cost of the system infrastructure should be reduced. The current trend to reduce the cost of the systems is to use the wireless infrastructures already deployed for communications as landmarks for positioning. Among the multitude of available technologies for communications such us LTE, WiFi, Bluetooth, Wireless Sensor Networks (WSN) or Ultra Wide Band (UWB), the WiFi technology is the most commonly employed because it is already worldwide deployed. Although WSNs are also commonly used due to its key role in the Internet of the Things (IoT) and the future of smart cities. Similarly, the development of the Microelectromechanical Systems (MEMS) provide us with low cost inertial sensors that can also estimate the position of a pedestrian without the need of any infrastructure in the building. Note that most of these technologiesare already available in nowadays smartphones, converting the smartphone in the perfect device for mass market positioning systems. Numerous studies have attempted to review the current state of art of IPS. Since the first review in 2001 by [PERSON] et al. [2], many new reviews have appeared. For example in 2002, [PERSON] et al. [3] presented a review of the state of the art focusing on systems for indoor environments. More recent revisions are presented in [4; 5] covering hybrid systems of network based technologies. Similarly, inertial based systems are reviewed in [6]. There are other surveys that cover specific kinds of systems, like fingerprinting [7; 8], or a specific technology, like UWB [9]. Other authors reviewed the state of the art from a bayesian estimation perspective as in [10] or in [11]. Despite the numerous surveys in IPS, none of them performed a comprehensive analysis of the state of the art of IPS focusing on its application to the mass market. In this work we overview the state of the art of IPS analysing the advantages and disadvantages of the reviewed systems and its applicability to mass market applications. First of all, we classify and review individual IPS and then we review the most promising hybrid methods for mass market applications. Traditionally IPS systems can be classified into three groups:  
* **Network based systems:** these systems are build on the top of a wireless network deployed in the scenario and use the information of the wireless signals to estimate the position of the user carrying a wireless device.