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Distance-based Indoor Localization using Empirical Path Loss Model and RSSI in Wireless Sensor Networks Dwi Joko Suroso; Muhammad Arifin; Panarat Cherntanomwong
Journal of Robotics and Control (JRC) Vol 1, No 6 (2020): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.1638

Abstract

Wireless sensor networks (WSNs) have a vital role in indoor localization development. As today, there are more demands in location-based service (LBS), mainly indoor environments, which put the researches on indoor localization massive attention. As the global-positioning-system (GPS) is unreliable indoor, some methods in WSNs-based indoor localization have been developed. Path loss model-based can be useful for providing the power-distance relationship the distance-based indoor localization. Received signal strength indicator (RSSI) has been commonly utilized and proven to be a reliable yet straightforward metric in the distance-based method. We face issues related to the complexity of indoor localization to be deployed in a real situation. Hence, it motivates us to propose a simple yet having acceptable accuracy results. In this research, we applied the standard distance-based methods, which are is trilateration and min-max or bounding box algorithm. We used the RSSI values as the localization parameter from the ZigBee standard. We utilized the general path loss model to estimate the traveling distance between the transmitter (TX) and receiver (RX) based on the RSSI values. We conducted measurements in a simple indoor lobby environment to validate the performance of our proposed localization system. The results show that the min-max algorithm performs better accuracy compared to the trilateration, which yields an error distance of up to 3m.  By these results, we conclude that the distance-based method using ZigBee standard working on 2.4 GHz center frequency can be reliable in the range of 1-3m. This small range is affected by the existence of interference objects (IOs) lead to signal multipath, causing the unreliability of RSSI values. These results can be the first step for building the indoor localization system, which low-cost, low-complexity, and can be applied in many fields, especially indoor robots and small devices in internet-of-things (IoT) world’s today.
Performance Comparison of Several Range-based Techniques for Indoor Localization Based on RSSI Dwi Joko Suroso; Farid Yuli Martin Adiyatma; Ahmad Eko Kurniawan; Panarat Cherntanomwong
International Journal on Information and Communication Technology (IJoICT) Vol. 7 No. 1 (2021): June 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21108/ijoict.v7i1.550

Abstract

The classical rang-based technique for position estimation is still reliably used for indoor localization. Trilateration and multilateration, which include three or more references to locate the indoor object, are two common examples. These techniques use at least three intersection-locations of the references' distance and conclude that the intersection is the object's position. However, some challenges have appeared when using a simple power-to-distance parameter, i.e., received signal strength indicator (RSSI). RSSI is known for its fluctuated values when used as the localization parameter. The improvement of classical range-based has been proposed, namely min-max and iRingLA algorithms. These algorithms or methods use the approximation in a bounding-box and rings for min-max and iRingLA, respectively. This paper discusses the comparison performance of min-max and iRingLA with multilateration as the classical method. We found that min-max gives the best performance, and in some positions, iRingLA gives the best accuracy error. Hence, the approximation method can be promising for indoor localization, especially when using a simple and straightforward RSSI parameter.
Spatial aliasing effects on beamforming performance in large-spacing antenna array Dwi Joko Suroso; Deepak Gautam; Sunarno Sunarno
Communications in Science and Technology Vol 4 No 1 (2019)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (631.043 KB) | DOI: 10.21924/cst.4.1.2019.109

Abstract

In the next wireless communication generation, 5G, it is obvious to employ the half-spacing antenna elements as high-resolution antenna array. However, to compensate the lower aperture from short-spacing elements, the number of antennas should be grown larger. It will be costly and increase complexity in terms of antenna array analysis. In this paper, the aliasing effects on beamforming of antenna array geometry utilizes inter-element spacing more than half-lambda. The antenna geometry of linear, circular and planar will be explored in this paper and the center frequency for simulation is 60 GHz. It is also due the fact that many researchers on 5G believe 60 GHz will be employed as 5G frequency band. 60 GHz is truly higher than today Long-term-evolution (LTE) working frequency and it is really challenging to its signal model due to small wavelength and its effective signal working distance as effect of rain attenuation, etc. As our preliminary results, linear array, which only considers the azimuthal, the spatial aliasing appears in the inter-element distance more than 1-lambda. The circular and planar consider the azimuth and elevation properties of incoming signals. In circular array, the power angular of a signal can be detected accurately applying the 3-sector antenna pattern. When the inter-element distance grows more than 1.5 lambda, the spatial aliasing which appear to be side lobe with similar power angular dominate the incoming signal detection. The result shows us that employing the 2-lambda distance or more will be useless. Planar array which actually a 2-axis linear array give unexpected results, most of detections are inaccurate and power angular also low. This concludes that spatial aliasing effects will degrade the beamforming performance due to confusion between real signal and fake signal resulting from similar values of array factor.
Random Forest-based Fingerprinting Technique for Device-free Indoor Localization System Dwi Joko Suroso; Refa Rupaksi; Aditya Bagus Krisnawan; Nur Abdillah Siddiq
Indonesian Journal of Computing, Engineering and Design (IJoCED) Vol 3 No 2 (2021): IJoCED
Publisher : Faculty of Engineering and Technology, Sampoerna University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35806/ijoced.v3i2.172

Abstract

The device-free indoor localization (DFIL) research is gaining attention due to the popularity of location-based service (LBS)-based advertisement. In DFIL, a user or an object does not need to bring any device to be localized. In this paper, we propose the Wi-Fi-based DFIL and the random forest algorithm for the fingerprint-based technique. The simple parameter commonly used in indoor localization is the Received Signal Strength Indicator (RSSI). We apply the fingerprint technique because of its reliability to handle the RSSI fluctuation and time-varying effect in a static indoor environment. We conducted an actual measurement campaign to observe the DFIL's implementation visibility. The DFIL system works by comparing the database fingerprint in an empty open office with the database in which a person is inside the measurement area without bringing any devices. Thus, we have the device-free RSSI database for fingerprint technique from both empty rooms and RSSI affected by a person inside the room. We validated the random forest algorithm results by comparing them with the k-nearest neighbor (kNN) and artificial neural network (ANN). The results show that our proposed system's accuracy is better than kNN and ANN with a mean error of 0.63 m than kNN with 0.80 m and ANN with 1.01 m. Meanwhile, the precision of the random forest is 0.63 m, whereas kNN and ANN are 0.67 m and 0.80 m, showing that the random forest performed better. We concluded that our simple DFIL system is visible to apply with acceptable accuracy performance.
A Simulation-Based Study of Maze-Solving-Robot Navigation for Educational Purposes Ismu Rijal Fahmi; Dwi Joko Suroso
Journal of Robotics and Control (JRC) Vol 3, No 1 (2022): January
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v3i1.12241

Abstract

The point of education in the early stage of studying robotics is understanding its basic principles joyfully. Therefore, this paper creates a simulation program of indoor navigations using an open-source code in Python to make navigation and control algorithms easier and more attractive to understand and develop. We propose the maze-solving-robot simulation as a teaching medium in class to help students imagine and connect the robot theory to its actual movement. The simulation code is built for free to learn, improve, and extend in robotics courses or assignments. A maze-solving robot study case is then done as an example of implementing navigation algorithms. Five algorithms are compared, such as Random Mouse, Wall Follower, Pledge, Tremaux, and Dead-End Filling. Each algorithm is simulated a hundred times in every type of the proposed mazes, namely mazes with dead ends, loops only, and both dead ends and loops. The observed indicators of the algorithms are the success rate of the robots reaching the finish lines and the number of steps taken. The simulation results show that each algorithm has different characteristics that should be considered before being chosen. The recommendation of when-to-use the algorithms is discussed in this paper as an example of the output simulation analysis for studying robotics.