Research and Prospect on Key Technologies of Indoor Positioning Based on Visible Light Communication

Indoor positioning has become a research hotspot because of its important application value in industrial production and daily life. Traditional wireless positioning technologies such as Wi Fi and Bluetooth are difficult to achieve high-precision indoor positioning due to electromagnetic interference and multipath effect. The modulated white LED can not only meet the needs of lighting, but also transmit the location information to achieve high-precision indoor positioning. This paper first introduces several modulation methods commonly used in visible light positioning system, compares the characteristics of different modulation methods, and proposes a modulation method suitable for visible light positioning; Then, two demodulation methods of the visible light positioning system are introduced and discussed; After that, several visible light location algorithms are introduced, and the performance of each algorithm is analyzed in detail; Finally, the problems in visible light positioning are discussed and prospected.

Self-Contained Pedestrian Tracking With Mems Sensors

Due to the limitations of current indoor wireless positioning technologies, a novel positioning/tracking solution has to be explored and developed, in order to locate a person anywhere anytime without any infrastructure. The purpose of this thesis is to present the result of the first phase of a long-period research to find such a solution and develop a practical system. In this thesis, using inertial sensors for positioning of people is selected to replace wireless solutions, considering the development of micro-electromechanical systems. A sensing module consisting of accelerometers, rate gyroscopes and magnetometers used to monitor human kinetics. In order to make this proposal practical, a synergy of existing strapdown inertial navigation and pedestrian dead-reckoning is proposed to improve the accuracy of positioning. Furthermore, the cyclic alternation of stance phase and swing phase in human walking is used to reduce errors accumulating during projection and integration of sensed accelerometer signals. Other than the improvement of some existing methods to detect stance phase and reset the velocity, several new methods are proposed to remove the integral drift during both phases of a human stride. The algorithm to calculate heading of on the sensing module is also deduced to limit the integral drift of rate gyroscopes. All the methods and algorithms are applied in field experiments with carefully chosen sensing module mounted on human footwear. The results show promising accuracy of tracking, hence validate the feasibility of self-contained pedestrian tracking system with inertial sensors. Further work, especially with map correlation and particle filtering, will be done in the coming phases of the project to make the system applicable both outdoor and indoor.

Self-Contained Pedestrian Tracking With Mems Sensors

Due to the limitations of current indoor wireless positioning technologies, a novel positioning/tracking solution has to be explored and developed, in order to locate a person anywhere anytime without any infrastructure. The purpose of this thesis is to present the result of the first phase of a long-period research to find such a solution and develop a practical system. In this thesis, using inertial sensors for positioning of people is selected to replace wireless solutions, considering the development of micro-electromechanical systems. A sensing module consisting of accelerometers, rate gyroscopes and magnetometers used to monitor human kinetics. In order to make this proposal practical, a synergy of existing strapdown inertial navigation and pedestrian dead-reckoning is proposed to improve the accuracy of positioning. Furthermore, the cyclic alternation of stance phase and swing phase in human walking is used to reduce errors accumulating during projection and integration of sensed accelerometer signals. Other than the improvement of some existing methods to detect stance phase and reset the velocity, several new methods are proposed to remove the integral drift during both phases of a human stride. The algorithm to calculate heading of on the sensing module is also deduced to limit the integral drift of rate gyroscopes. All the methods and algorithms are applied in field experiments with carefully chosen sensing module mounted on human footwear. The results show promising accuracy of tracking, hence validate the feasibility of self-contained pedestrian tracking system with inertial sensors. Further work, especially with map correlation and particle filtering, will be done in the coming phases of the project to make the system applicable both outdoor and indoor.

Indoor location tracking pegawai berbasis Android menggunakan algoritma k-nearest neighbor

Dalam sebuah perusahaan besar biasanya memiliki banyak karyawan. Tetapi jumlah karyawan yang banyak tersebut dapat menyebabkan kurangnya pengawasan dan pengendalian terhadap sistem kerja pegawai. Tumbuhnya teknologi informasi memberikan peluang untuk menyelesaikan permasalahan ini. Salah satu teknologi yang bisa digunakan adalah wireless positioning sytem (WPS). Pemanfaatan teknologi ini memberikan solusi dengan memberikan informasi posisi pegawai berdasarkan kekuatan sinyal WiFi yang dipancarkan dari telepon genggam. Penelitian ini bertujuan untuk merancang sistem indoor location tracking berbasis Android dengan algoritma k-nearest neighbor (K-NN). Pada sistem ini, proses rancang bangun dilakukan melalui tahapan perhitungan pembacaan posisi dari client, perbandingan database dengan menggunakan algoritma K-NN, dan metode fingerprint localization sehingga informasi koordinat client dapat ditampilkan dalam peta koordinat secara real-time. Berdasarkan hasil pengujian, rancang bangun sistem yang telah dilakukan memiliki keakuratan sangat baik. Rata rata akurasi data besar dari 60% dengan kondisi client yang bergerak aktif maupun diam di tempat.

Study of RSS-Based Indoor Positioning System for Target Using Visible Light Communication

An optical wireless positioning system that uses white light-emitting diodes (LEDs) based on Visible Light Communication (VLC) is presented in this paper. In the proposed system, four LEDs are employed for illumination and communication. The trilateration technique is used for determining the receiver's location and the practical Received Signal Strength (RSS) measurements are used for distance estimation. The impact of ambient light on Signal-to-Noise-Ratio (SNR) is studied by taking into consideration the first-order light reflection off of the ceiling, floor, and walls for channel modeling with both direct and indirect sunlight exposure. A modeling equation from the RSS measurements is proposed. The results show that the illuminance in all of the places in the room can be satisfied. Furthermore, the average positioning error by adopting the derived equation and trilateration technique was an error of less than 3 cm.

Self-powered seesaw structured spherical buoys based on hybrid triboelectric-electromagnetic nanogenerator for sea surface wireless positioning

The rapid development of Internet of Things brings increasing attention on the harvesting of distributed sustainable energy. Recently, study on triboelectric nanogenerators (TENG) in collecting low-frequency and irregular amplitude ocean...