Conclusion and Future Work

Since IEEE wireless protocol was released about ten years ago, Wi-Fi technical standards have been well developed and widely used due to the high speed, wireless connectivity and large coverage of the Wi-Fi technology. Nowadays the demand for real-time location information of mobile users is unprecedented. For outdoor environments, using GPS can achieve high accuracy positioning results.

However, in indoor environments, due to the attenuation or obstruction of GPS signals, GPS technology cannot be used effectively. Therefore, Wi-Fi based positioning technology has been researched and developed for indoor environments.In this thesis, the huge market potential and rapid development of smartphones technologies were briefly assessed. It is concluded that the integration of the smartphones and Wi-Fi for indoor positioning is a mainstream direction in research and industry commercialization. The main challenges for indoor environment are discussed with the conclusion that the fingerprint technique based on RSS is the optimal solution and the smartphones is the most suitable mobile device due to its wide usage. Commonly used estimation methods and algorithms of fingerprint technique are reviewed.We successfully implemented a Wi-Fi based indoor positioning system using a smartphone and the fingerprint-based positioning method.

A number of case studies were designed and field experiments were conducted using various mobile platforms (i.e. smartphone, iPad and laptop) and the development and requirements of hardware and software systems were described.The statistical result of the positioning errors(the maximum and minimum errors were 4.79 m and 0.58 m respectively) in the specific indoor environment. This is compared against our testing system results of 2 m, which is, more precisely, the spatial resolution of the best matching algorithm. The performances of both systems were affected by the quality of the RSS observations collected from a smartphone. The current smartphones have limitations on the quality of Wi-Fi adapters. It is expected that better quality and proper sized Wi-Fi adapters will be available in smartphones in future. The spatial resolution of the proposed indoor positioning system can be further improved by setting up more complex indoor environment, and increasing the number of APs or combining other types of sensors into the smartphone.

Several aspects can be further explored to enhance the performance of the proposed Wi-Fi based positioning system for future work. Three main aspects are listed as follows:

1. Setup RSS database for different brand Wi-Fi adapters: The proposed indoor positioning system is device-dependent, thus different brand Wi-Fi adapters with various receiving capabilities need to be tested. The fingerprinting process must be done for each type of Wi-Fi adapter. Further research needs to be carried out to investigate new methods to reduce the impact of the device-dependent errors. High stability is expected for other mobile devices rather than Samsung smartphone.
2. Multi-sensor fusion: most current smartphones are equipped with other types of sensors such as accelerometer, gyroscope and digital compass, in addition to the built-in Wi-Fi adapter. Data obtained from accelerometers, gyroscope and digital compass could be very useful sources of information for indoor positioning since it can provide auxiliary data such as speed and orientation of movement. The improved positioning system can therefore make best use of the observations from these sensors to improve the accuracy of the position estimates. New algorithms for the integrated system need to be developed and its performance needs to be assessed.
3. Smartphone-based server or cloud server: The positioning server of the proposed system is configured at a remote laptop. With the development of the CPU computation power and memory space of smartphones, we could setup both the positioning server and the RSS calibration database into a smartphone to decrease the data transmission time. This is important for the case of multiple clients. Moreover, we could also use cloud service, which has been popularly used in IT industry, as our positioning server. More research should be extended into the cloud service to enhance indoor positioning capability and performance.