Recently, with the development of the systems that support tracking of various objects and the component technology of Internet of Things (IoT), the use of tracking system is increasing in social infrastructures and various industrial sectors. With the application of the IT technology that can manage the movement of objects in real time in industrial sites, the sectors where the technology of tracking system can be applied are expanding. However, to satisfy the various demands of industrial sites, the existing tracking system has many technological problems. For example, due to the technological problems in solving spatial errors and errors related to time, there are limitations in introducing object-based tracking system in the medical industry or industrial sites with high risks, and these errors, when involved in service sectors, can seriously hurt customers’ reliability. Also, even in sectors where error range is not important, there are many problems such as high power consumption, high utilization of data, and the trouble of object tracking in some locations. Analyzing problems such as errors of tracking, power consumption, data use, and situations where object-tracking is not supported, this study tried to reduce error range and design and develop an intelligent smart tracking system that minimizes data use with low-power base.

Due to the recent technical development of an object tracking system and Internet of Everything (IOE), our social environment and almost every industry fields have adopted tracking system and applied IT technology where we can monitor conditions in real time. But many problems still need to solved with the current tracking system to satisfy various requirements for a variety of industry fields. For instance, object tracking has limitation to be adopted in military field since error range is a critical issue and also not only in medical but fields that are related directly to life or in service areas where they need to deal with tons of customers, the error range is a critical issue linked to customer reliability. This research presents smart middleware system which can effectively manage tracked objects to reduce errors through improved algorithm and analyzed result.

As population concentrates into cities cars have become main stream. This led to frequent complaints over securing enough space for vehicle operation, leading to conflict among residents and social issues. There is a need for a fundamental measure for resolving vehicle operation space issues. To that end, a "priority parking system for residents" has been introduced that supplies vehicle space to back alleys of residential areas in Korea and gives priority to residents so that conflict between neighbors is reduced and the demand for vehicle space is deterred. However, even after this law took effect there have been many illegal parking. Sometimes a mistake by the manager led to toeing of a resident's car. As such, this paper suggests a high efficiency, high function system that is based on IoT and RFID for an automated vehicle space management system with comprehensive middleware system. This helps prevent illegal parking in advance and reduce the possibilities of managers' mistakes.

Existing tracking systems are insufficient to provide services that customers can be satisfied with. Competition between logistics companies is increasing and customers of such logistics services are increasing requiring more. But at present, the response to such requests can hardly be seen as timely or appropriate. Since customers of logistics services not only wish to receive their ordered products but also check where their item is and how the delivery is being processed, companies provide location information over the internet. But updates on such information is hardly in real time, leading to a discrepancy between information online and actual location. Existing systems cannot address such issues perfectly, nor are there technologies that can meet such needs. As such, this paper suggests a system that can improve customer services and convenience, work efficiency and profitability for the logistics company. The system was designed and developed as a high-functioning intellectual App Multi Tracking System that is based on IoT and RTLS, which sets it apart from existing tracking systems.

With the rapid development of the IoT market many institutions are researching and developing various integrated IOT service platforms.Among them the development of IoT based tracking system requires a platform environment that can check in real time the target-oriented logistics movement status in industrial sites and social environments and manage resources.Previous related researches studied about particular single object tracking and about establishing a linkage process, but there were no studies about systems using Multiple Tracking System that target a variety of objects to establish a total task process such as for materials, personnel, and operations and process management.The study developed an efficient target-oriented smart integrated multiple tracking system that looks up object location based on real time and guarantees the accuracy and reliability of logistics location and resource management by combining the function of multiple tracking system.