Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716194
A. Ramadhani, A. Firdausi, Umaisaroh Umaisaroh, M. Alaydrus
The improvement of wireless communication is in line with the need for data transfer speed. The requirement of high capacity, big coverage, low energy consumption, and affordable equipment is urgently need. A high gain microstrip antenna is required. One of the suitable designs is using reflectarray antenna. Reflectarray has been researched to arrange the phase distribution by adjusting the unit cell elements. Moreover, by applying beamforming technique, the focusing beam direction of the antenna can be improved. This paper aims a design of a reflectarray antenna with beamforming that for 28 GHz frequency. The reflectarray antenna unit cell model consists of a square patch with cross and square slot. A complete reflectarray consisting of $7 times 7$ unit cells is simulated with a horn antenna feed. The simulation results show a gain of 19.33 dB with a power shift about 6 dB when compared to the measurement results. For the beamforming direction in the horizontal and vertical radiation pattern, a shift of about 6° is seen. If the beamforming simulation results are seen at a position of 24°, then the beamforming measurement results are at a position of 30°.
{"title":"Design of Cross and Square Slot with Beamforming for Microstrip Reflectarray Antenna at 28 GHz","authors":"A. Ramadhani, A. Firdausi, Umaisaroh Umaisaroh, M. Alaydrus","doi":"10.1109/QIR54354.2021.9716194","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716194","url":null,"abstract":"The improvement of wireless communication is in line with the need for data transfer speed. The requirement of high capacity, big coverage, low energy consumption, and affordable equipment is urgently need. A high gain microstrip antenna is required. One of the suitable designs is using reflectarray antenna. Reflectarray has been researched to arrange the phase distribution by adjusting the unit cell elements. Moreover, by applying beamforming technique, the focusing beam direction of the antenna can be improved. This paper aims a design of a reflectarray antenna with beamforming that for 28 GHz frequency. The reflectarray antenna unit cell model consists of a square patch with cross and square slot. A complete reflectarray consisting of $7 times 7$ unit cells is simulated with a horn antenna feed. The simulation results show a gain of 19.33 dB with a power shift about 6 dB when compared to the measurement results. For the beamforming direction in the horizontal and vertical radiation pattern, a shift of about 6° is seen. If the beamforming simulation results are seen at a position of 24°, then the beamforming measurement results are at a position of 30°.","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115780350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716163
Farhan P. Putra, Prima Dewi Purnamasari, A. A. P. Ratna, Lea Santiar
In this paper, a study was conducted for a hybrid model for Multilayer Perceptron (MLP) with Particle Swarm optimization (PSO). The PSO was used to replace the Backpropagation method for the weight optimization. The comparison was conducted between MLP-BPNN and MLPPSO for an automated essay grading system for Japanese language exam. The MLP-PSO model achieved a more accurate but less stable result. The MLP-PSO model with 10 particles trained for 15 steps achieves the best result out of the two MLP-PSO models tested, with an average 8.48% error for the grade population. Compared to the MLP-PSO model, it was discovered that MLP-BPNN with Adam optimizer achieves better overall performance and results concerning both the accuracy and the stability of the model.
{"title":"Comparison of MLP-BPNN and MLP-PSO for Automatic Essay Grading System for Japanese Language Exam","authors":"Farhan P. Putra, Prima Dewi Purnamasari, A. A. P. Ratna, Lea Santiar","doi":"10.1109/QIR54354.2021.9716163","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716163","url":null,"abstract":"In this paper, a study was conducted for a hybrid model for Multilayer Perceptron (MLP) with Particle Swarm optimization (PSO). The PSO was used to replace the Backpropagation method for the weight optimization. The comparison was conducted between MLP-BPNN and MLPPSO for an automated essay grading system for Japanese language exam. The MLP-PSO model achieved a more accurate but less stable result. The MLP-PSO model with 10 particles trained for 15 steps achieves the best result out of the two MLP-PSO models tested, with an average 8.48% error for the grade population. Compared to the MLP-PSO model, it was discovered that MLP-BPNN with Adam optimizer achieves better overall performance and results concerning both the accuracy and the stability of the model.","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116517153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716172
H. Inokawa, Yuto Goi, Toshiaki Yorigami, Kyohei Shirotori, H. Satoh, M. Tomita, T. Matsuki, H. Ikeda, Takanobu Watanabe
Thermoelectric characteristics of phosphorus-doped silicon (Si) nanowire (NW) are evaluated in terms of the substrate bias effect. It is found that the narrower wire is more sensitive to the substrate voltage presumably due to the field crowding effect. In case of 200-nm-wide NW, application of 40 V to the substrate increases the NW conductance by a factor of 55.4, and leads to × 25.9 improvement in power generation, even though the Seebeck coefficient is reduced to 74%. The result suggests that the performance of the Si thermoelectric generator could be improved or optimized by the substrate bias control.
{"title":"Substrate Bias Effect on SOI-based Thermoelectric Power Generator","authors":"H. Inokawa, Yuto Goi, Toshiaki Yorigami, Kyohei Shirotori, H. Satoh, M. Tomita, T. Matsuki, H. Ikeda, Takanobu Watanabe","doi":"10.1109/QIR54354.2021.9716172","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716172","url":null,"abstract":"Thermoelectric characteristics of phosphorus-doped silicon (Si) nanowire (NW) are evaluated in terms of the substrate bias effect. It is found that the narrower wire is more sensitive to the substrate voltage presumably due to the field crowding effect. In case of 200-nm-wide NW, application of 40 V to the substrate increases the NW conductance by a factor of 55.4, and leads to × 25.9 improvement in power generation, even though the Seebeck coefficient is reduced to 74%. The result suggests that the performance of the Si thermoelectric generator could be improved or optimized by the substrate bias control.","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125843398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716162
D. Sudiana, M. Rizkinia, Ilham Mulya Rafid
This research discusses the design and development of an automatic physiognomy system to determine a person’s tendencies based on the features of its face. Physiognomy itself is a method of predicting a person’s characteristics based on their facial features. Each facial feature has its uniqueness and characteristics, such as variations in distance, overall shape, and size. The facial image as input data is processed in every system step. Finally, the system displays the personality of that person. Simulations show that each algorithm can perform its respective functions well. The simulation results show that the combination of extracting facial features using the Active Appearance Model and Convolutional Neural Network for solving classification problems produces a very good number of personality traits predictions with each model accuracy value between 0.8 to 1, or 0.8797 on average. In addition, the model made proved to produce a good performance for the classification process with a true positive rate between 0.8834 to 1, or 0.9417 on average. This method can also detect many personality traits, with 28 personality traits that can be detected.
{"title":"Automatic Physiognomy System using Active Appearance Model and Convolutional Neural Network","authors":"D. Sudiana, M. Rizkinia, Ilham Mulya Rafid","doi":"10.1109/QIR54354.2021.9716162","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716162","url":null,"abstract":"This research discusses the design and development of an automatic physiognomy system to determine a person’s tendencies based on the features of its face. Physiognomy itself is a method of predicting a person’s characteristics based on their facial features. Each facial feature has its uniqueness and characteristics, such as variations in distance, overall shape, and size. The facial image as input data is processed in every system step. Finally, the system displays the personality of that person. Simulations show that each algorithm can perform its respective functions well. The simulation results show that the combination of extracting facial features using the Active Appearance Model and Convolutional Neural Network for solving classification problems produces a very good number of personality traits predictions with each model accuracy value between 0.8 to 1, or 0.8797 on average. In addition, the model made proved to produce a good performance for the classification process with a true positive rate between 0.8834 to 1, or 0.9417 on average. This method can also detect many personality traits, with 28 personality traits that can be detected.","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130103699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/qir54354.2021.9716182
{"title":"[QIR 2021 Front cover]","authors":"","doi":"10.1109/qir54354.2021.9716182","DOIUrl":"https://doi.org/10.1109/qir54354.2021.9716182","url":null,"abstract":"","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125302690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716187
Y. Rahayu, As Ibrahim
The fifth-generation (5G) communication shows the progress of the entire cellular network architecture. Indonesia has just launched the first 5G network on May 21, 2021, as a tangible manifestation of the leading digital telecommunication. The 5G band allocation used for the first deployment is in the medium frequency band (2-6 GHz). In this paper, the 5G high-frequency band (beyond 6 GHz) is used to design a MIMO antenna for future deployment. The MIMO antenna is designed for 5G applications working at a frequency of 38 GHz. This allocated frequency was also recommended by the Federal Communications Commission (FCC). The antenna was designed by using a patch in the form of an octagon ring with microstrip line feeding. MIMO technique is used to increase system capacity with a gain value above 10 dBi. Antenna MIMO is designed using a material substrate RT Duroid 5880 with $varepsilon r$ = 2.2, thickness (h) = 0.254 mm, and tan $delta = 0.0009$. From the simulation, the S11 reached -29.5 dB, a gain of 13.44 dBi, mutual coupling below -20 dB, and bandwidth of 14.002 GHz (31.008 GHz to 45.01 GHz).
{"title":"Investigation on Simulation-Based Octagonal Ring MIMO Antenna for 5G Applications","authors":"Y. Rahayu, As Ibrahim","doi":"10.1109/QIR54354.2021.9716187","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716187","url":null,"abstract":"The fifth-generation (5G) communication shows the progress of the entire cellular network architecture. Indonesia has just launched the first 5G network on May 21, 2021, as a tangible manifestation of the leading digital telecommunication. The 5G band allocation used for the first deployment is in the medium frequency band (2-6 GHz). In this paper, the 5G high-frequency band (beyond 6 GHz) is used to design a MIMO antenna for future deployment. The MIMO antenna is designed for 5G applications working at a frequency of 38 GHz. This allocated frequency was also recommended by the Federal Communications Commission (FCC). The antenna was designed by using a patch in the form of an octagon ring with microstrip line feeding. MIMO technique is used to increase system capacity with a gain value above 10 dBi. Antenna MIMO is designed using a material substrate RT Duroid 5880 with $varepsilon r$ = 2.2, thickness (h) = 0.254 mm, and tan $delta = 0.0009$. From the simulation, the S11 reached -29.5 dB, a gain of 13.44 dBi, mutual coupling below -20 dB, and bandwidth of 14.002 GHz (31.008 GHz to 45.01 GHz).","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123095317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716175
Isla Madinah Hakim, Zaqiatud Darojah, Eny Kusumawati, E. S. Ningrum
Bearing is a machine part that has a function to keep the shaft always rotating or moving linearly to the axis of the shaft and its path. Bearings are often found in automotive equipment and home appliances, one of them is the bearing that has found in a single-phase induction motor (water pump). But, until now the largest percentage of induction motor faults occurs in bearings. Therefore, an accurate system of bearing faults detection is the key to protecting an induction motor from such any faults. In this study, we proposed bearing faults detection on a single-phase induction motor with water loads and based on Internet of Things (IoT). This system used multi-sensors, i.e. a temperature sensor, a current sensor, and a vibration sensor. Some processes in this bearing faults detection system are feature extraction process using Empirical Mode Decomposition (EMD) and pattern recognition process using Backpropagation Neural Network (BNN). Then the results from pattern recognition is displayed through the Internet of Things (IoT) system. The results of this project show that EMD can decompose the vibration signal and BNN is able to classify signals with 100% accuracy of current signals and 98% for vibration signals.
{"title":"Multi Sensing on Bearing Faults Detection with Internet of Things (IoT) based","authors":"Isla Madinah Hakim, Zaqiatud Darojah, Eny Kusumawati, E. S. Ningrum","doi":"10.1109/QIR54354.2021.9716175","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716175","url":null,"abstract":"Bearing is a machine part that has a function to keep the shaft always rotating or moving linearly to the axis of the shaft and its path. Bearings are often found in automotive equipment and home appliances, one of them is the bearing that has found in a single-phase induction motor (water pump). But, until now the largest percentage of induction motor faults occurs in bearings. Therefore, an accurate system of bearing faults detection is the key to protecting an induction motor from such any faults. In this study, we proposed bearing faults detection on a single-phase induction motor with water loads and based on Internet of Things (IoT). This system used multi-sensors, i.e. a temperature sensor, a current sensor, and a vibration sensor. Some processes in this bearing faults detection system are feature extraction process using Empirical Mode Decomposition (EMD) and pattern recognition process using Backpropagation Neural Network (BNN). Then the results from pattern recognition is displayed through the Internet of Things (IoT) system. The results of this project show that EMD can decompose the vibration signal and BNN is able to classify signals with 100% accuracy of current signals and 98% for vibration signals.","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117023160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716177
A. F. Fauzi, I. G. D. Nugraha
AMI has been one of the leading technologies for Smart Grid. AMI utilized various network technologies to enable two-way communication for Smart Grid. AMI also enables real-time measurement that collects the electricity data from the user. This study utilizes LoRaWAN for the AMI and collects the electricity data. We focus on developing the web dashboard that visualizes the data from the LoRaWAN based AMI network. In addition, we utilize the anomaly detection module to analyze the collected data. From our experiment, we conduct pre-process for converting the LoRaWAN data. The result shows that the converted data is similar to actual data, and the accuracy of anomaly detection is 89%
{"title":"Implementation and Evaluation for Monitoring System in Electrical Meter based on LoRaWAN Network","authors":"A. F. Fauzi, I. G. D. Nugraha","doi":"10.1109/QIR54354.2021.9716177","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716177","url":null,"abstract":"AMI has been one of the leading technologies for Smart Grid. AMI utilized various network technologies to enable two-way communication for Smart Grid. AMI also enables real-time measurement that collects the electricity data from the user. This study utilizes LoRaWAN for the AMI and collects the electricity data. We focus on developing the web dashboard that visualizes the data from the LoRaWAN based AMI network. In addition, we utilize the anomaly detection module to analyze the collected data. From our experiment, we conduct pre-process for converting the LoRaWAN data. The result shows that the converted data is similar to actual data, and the accuracy of anomaly detection is 89%","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121567689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716203
Elang Barruna, J. Sulistianto, N. R. Poespawati
Perovskite solar cells called fourth-generation photovoltaic technology have developed rapidly because of their outstanding efficiency and low-temperature manufacturing process. One of the layers used in perovskite-based solar cells is the counter electrode. Activated carbon is one type of carbon that has the potential to replace metal as an electrode material due to its good chemical stability, high electrical conductivity, low cost, and abundance. Apart from that, CuSCN is a famous hole transport material because of its wide bandgap, good stability, and high hole mobility. Many studies have tried to combine the electrode material with hole transfer material in an effort to improve the device performance. This paper presents an investigation of the perovskite solar cell device performance with CuSCN-incorporated carbon electrodes. Concentration variations of CuSCN in carbon electrodes were carried out with values of 0.5%, 1%, and 2%. Different levels of CuSCN concentration in carbon electrodes resulted in different properties and performance of the device. Adding CuSCN with a concentration of 1% in carbon electrode yielded the best device performance with an efficiency of 0.0035%, fill factor of 0.32, $mathrm{I}_{mathrm{s}mathrm{c}}$ of 0.11 mA, and $mathrm{V}_{mathrm{o}mathrm{c}}$ of 0.14 V. Correctly combining the carbon material with hole transport material served a better the energy level alignment and hole transport properties.
{"title":"The Effect of CuSCN Concentration Variations in Activated Carbon Electrode on the Perovskite Solar Cells Performance","authors":"Elang Barruna, J. Sulistianto, N. R. Poespawati","doi":"10.1109/QIR54354.2021.9716203","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716203","url":null,"abstract":"Perovskite solar cells called fourth-generation photovoltaic technology have developed rapidly because of their outstanding efficiency and low-temperature manufacturing process. One of the layers used in perovskite-based solar cells is the counter electrode. Activated carbon is one type of carbon that has the potential to replace metal as an electrode material due to its good chemical stability, high electrical conductivity, low cost, and abundance. Apart from that, CuSCN is a famous hole transport material because of its wide bandgap, good stability, and high hole mobility. Many studies have tried to combine the electrode material with hole transfer material in an effort to improve the device performance. This paper presents an investigation of the perovskite solar cell device performance with CuSCN-incorporated carbon electrodes. Concentration variations of CuSCN in carbon electrodes were carried out with values of 0.5%, 1%, and 2%. Different levels of CuSCN concentration in carbon electrodes resulted in different properties and performance of the device. Adding CuSCN with a concentration of 1% in carbon electrode yielded the best device performance with an efficiency of 0.0035%, fill factor of 0.32, $mathrm{I}_{mathrm{s}mathrm{c}}$ of 0.11 mA, and $mathrm{V}_{mathrm{o}mathrm{c}}$ of 0.14 V. Correctly combining the carbon material with hole transport material served a better the energy level alignment and hole transport properties.","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122878225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-13DOI: 10.1109/QIR54354.2021.9716178
Lisa Kristiana, Nurjana Ariffilah Idris, A. Manurung, A. Darlis, Irma Amelia Dewi, Lita Lidyawati
A Flying Ad-hoc network (FANET) emerges recently due to its flexibility in terms of flying tracks and movements. As one type of Unmanned Aerial Vehicles (UAVs), a drone can be considered as the low-cost platform to implement the FANET. In a particular case, the flying tracks and movements of a drone can encounter inevitable obstacles such as building construction and any random objects. Thus, this paper focused on the obstacle issue in drone’s movements and proposed the feasibility of Sensor Fusion algorithm to distinguish the obstacle in the indoor environment. Under two conditions: single and multiple obstacles scenarios, the autonomous drone implementing Kalman Filter in Sensor Fusion experienced the real time response linearly as the distance increases.
{"title":"Obstacle Awareness System of An Indoor UAV with Multi-Sensor Fusion Algorithm","authors":"Lisa Kristiana, Nurjana Ariffilah Idris, A. Manurung, A. Darlis, Irma Amelia Dewi, Lita Lidyawati","doi":"10.1109/QIR54354.2021.9716178","DOIUrl":"https://doi.org/10.1109/QIR54354.2021.9716178","url":null,"abstract":"A Flying Ad-hoc network (FANET) emerges recently due to its flexibility in terms of flying tracks and movements. As one type of Unmanned Aerial Vehicles (UAVs), a drone can be considered as the low-cost platform to implement the FANET. In a particular case, the flying tracks and movements of a drone can encounter inevitable obstacles such as building construction and any random objects. Thus, this paper focused on the obstacle issue in drone’s movements and proposed the feasibility of Sensor Fusion algorithm to distinguish the obstacle in the indoor environment. Under two conditions: single and multiple obstacles scenarios, the autonomous drone implementing Kalman Filter in Sensor Fusion experienced the real time response linearly as the distance increases.","PeriodicalId":446396,"journal":{"name":"2021 17th International Conference on Quality in Research (QIR): International Symposium on Electrical and Computer Engineering","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116711698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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