Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
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An open source LoRa based vehicle tracking system
Get PDFThis work describes an open source tracking system that determines the location and speed of a vehicle in real-time. The system was inspired by the need to track tourist boats in UNESCO Kilim Karst Geoforest Park, Malaysia. Boats that travel too fast generate wakes that are suspected to cause ecological damage. In this work, geolocation information is provided by Arduino based transponders with Global Positioning System (GPS). Transponders periodically transmit location and speed data using LoRa through a gateway to a cloud server. On the server, open source software components implement a Geographical Information System (GIS) to manage the location and speed data for display and further analysis. The resulting prototype performed the required functions as expected
Experimental Determination of Penetration Loss into Multi-Storey Buildings at 900 and 1800MHz
Get PDFThis study presents building pentration loss into and around multi-storey buildings at 900 and 1800MHz based on experimental data obtained through drive test, using Test Mobile System (TEMS) investigation tools. The received signal level was measured inside and outside three buildings; the Senate building of the University of Lagos (B1), Mike Adenuga Towers (B2) and the Sapetro Towers (B3) located in Victoria Island, Lagos Nigeria. The building penetration loss (BPL) was derived from measurements, and the average and standard deviations of the BPL were computed. Results showed that the average BPL of 17.0dB and 13.8dB obtained from building B1 at 900 and 1800MHz, respectively, are comparatively higher than those of buildings B2 and B3. The standard deviation of the BPL shows an increase from 5.2dB at 900MHz to 7.8dB at 1800MHz for building B1, whereas it fell drastically from 8.65dB at 900MHz to 1.40dB at 1800MHz for B2, and a similar behaviour in B1 is seen for building B3 where it rises sharply from 1.55dB at 900MHz to 6.55dB at 1800MHz. This is in agreement with the general trend of increasing penetration loss with increase in frequency except for building B2 where an anomaly is observed. In order to examine the correlation between the measured and the predicted BPL, cubic regression was used to fit a third order polynomial to the measured BPL. Overrall, the fitted models could find useful applications in the design of novel and robust BPL models for modern multi-floored buildings
Android Application for Microcontroller-based Reservoir Water Level Monitoring
Get PDFA reservoir water level monitoring system was designed, constructed using a microcontroller and evaluated through functionality, reliability and accuracy. The monitoring system components consisted of a Gizduino microcontroller, Ethernet shield, serial camera and float switches which enabled the system to provide real time status and pictures of the reservoir. The monitoring system can be accessed using an Android application that can be installed in a compatible Android smartphone. An internet connection with a dedicated public IP was needed to broadcast the status and pictures of the reservoir. The specific monitoring system is fixed to a specific dam as it has a set of different float switches and camera. A back-up battery supply was integrated to the monitoring system to provide continuous power to the system. Fifty students evaluated the user acceptance of the water level monitoring system. According to the participants, the system was user-friendly, functional, reliable and accurate
Using SDN as a Technology Enabler for Distance Learning Applications
Get PDFThe number of students who obtained degrees via distance learning has grown considerably in the last few years. Services provided by distance learning systems are expected to be delivered in a fast and reliable way. However, as the number of users increases, so does the stress on the network. Software-Defined Networking, on the other hand, is a new technology that provides a rapid response to the ever-evolving requirements of today’s businesses. The technology is expected to enhance the overall performance of cloud services, including those provided by distance learning. This paper investigates the benefits of employing such a technology by educational institutions to provide quality services to the users. The results of the experiments show an improvement in performance of up to 11%, when utilizing the technology. In addition, we show how resource reservation features can be utilized to provide quality service to users depending on their role in the distance learning system
Effective Detection of Parkinson’s Disease at Different Stages using Measurements of Dysphonia
Get PDFThis paper addressees the problem of multiclass of Parkinson’s disease by the characteristic features of person’s voice. So we computed 22 dysphonia measures from 375 voice samples of healthy and people suffer from PD. We used the particle swarm optimization (PSO) feature selection method, with random forest and the linear discriminant analysis (LDA) along with the 4-fold cross validation analysis to classify the subjects in 4 classes according to the severity of symptoms. With a classification accuracy score of 95.2%. Promisingly, the proposed diagnosis system might serve as a powerful tool for diagnosing PD, and could also extended for other voice pathologies
Internet of Things Based Smart Health Monitoring of Industrial Standard Motors
Get PDFThe Industry 4.0 vision provides recommendations how companies can ease the challenges. In an industrial environment, it is beneficial to have a predictive approach to make smart industry using IoT. The Predictive approach includes automating the maintenance activities of machines which help to deliver safety, performance, customer experience, capacity, cost efficiency and sustainability of the key business assets. It helps to improve work force safety which reduces the need to access the infrastructure, develop technologies to enable activities to be remotely controlled from safe areas and automate processes to remove manual tasks and helps to increase infrastructure reliability. It also improves the precision and accuracy of data collection, introducing data analytics, removing human bias, improving reproducibility. This will improve information about asset condition, inform inspection and repair schedules based on asset risks. By implementing predictive and preventive maintenance, one can improve equipment life and avoid any unplanned maintenance activity and thus reducing unscheduled downtime. We in this work have an unit which could be easily attached to the motor units and this does not demand any wiring to carried out. The sensor monitor signals from the motor, accurately measuring key parameters at regular interval of time, as desired. And, the data is sent to the cloud, which in our case is adafruit. From there, the data is analysed and it produces meaningful information. The server then sends alert message to the users about critical data of machine. This will help in fixing any technical issue with ease without incurring much delay
An Improved Overlapping Clustering Algorithm to Detect Outlier
Get PDFMCOKE algorithm in identifying data objects to multi cluster is known for its simplicity and effectiveness. Its drawback is the use of maxdist as a global threshold in assigning objects to one or more cluster while it is sensitive to outliers. Having outliers in the datasets can significantly affect the effectiveness of maxdist as regards to overlapping clustering. In this paper, the outlier detection is incorporated in MCOKE algorithm so that it can detect and remove outliers that can participate in the calculation of assigning objects to one or more clusters. The improved MCOKE algorithm provides better identification of overlapping clustering results. The performance was evaluated via F1 score performance criterion. Evaluation results revealed that the outlier detection demonstrated higher accuracy rate in identifying abnormal data (outliers) when applied to real datasets
Determining Growing Season of Potatoes Based on Rainfall Prediction Result Using System Dynamics
Get PDFPotato has been and is a basic food for many countries. However, because of the uncertainty in rainfall patterns that have occurred since the existence of climate change make a significant impact on the outcome of potatoes production from year to year. Therefore, it needs the determination of new growing season period according to climate change. The determination of growing season is based on the result of rainfall prediction data using system dynamics ever done in previous studies to predictions of rainfall during the next five years starting in 2017-2021. Based on the modeling that has been done shows that early dry season ranges in mid-April to mid-May by the length of days in the growing season ranges from 162-192 days. The growing season prediction model has small error only about two dasarian. By the middle of the dry season, rainfall is expected to be very low which will make the potatoes into water deficit and will affect the harvest of potatoes plants which can be overcome with the irrigation system
Enzyme-Based Biosensors for Electrochemical Detection of Pesticides–A Mini Review
Get PDFDespite their important contribution in increasing crops production, most pesticides are harmful to humans and living beings and can persist in the environment over long a long duration. Traditional chromatographic methods of analysis are expensive and cumbersome. Biosensor technology appears therefore as an efficient and economical alternative for fast detection of pesticides. The devices are portable, rapid, and highly sensitive. Other important features of the devices are their relatively high sensistivity and low response time. Enzymatic biosensors for pesticide detection rely either on the inhibition mechanism or on the catalytic activity of the immobilized enzyme toward a specific pesticide. Metal and carbon based nanomaterials are being widely used as immobilization support owing to novel characteristics such as biocompatibility and enhanced electron transfer ability for sensitive electrochemical detection, among others. This review focusses on the electrochemical detection of organophosphorus pesticides, delineating the limit of detection and response time of biosensors toward a wide range of organophosphorus pesticides
A Packet Scheduling Scheme for Improving Real-time Applications Performance in Downlink LTE–advanced
Get PDFQuality of Service based packet scheduling is a key-feature of LTE-A mandating selection and transmission of individual user packets based on their priority. HARQ Aware Scheduling, Retransmission Aware Proportional Fair, Chase Combining Based Max C/I Scheduling and Maximum- Largest Weighted First (M-LWDF) are popular Packet Scheduling Algorithms (PSAs) developed to meet QoS requirements. In highly erroneous LTE-A cannel, M-LWDF is considered to be one of best PSA. To validate the performance of M-LWDF for the LTE-A channel, Mean User Throughout, and Fairness performance measures were evaluated for 3 different PSAs designed based on M-LWDF algorithm in this paper. A C++ based simulation results indicate the superiority of the PSA3 algorithm within the threshold of the performance measures against benchmarks. It has shown more efficiency and the performance of RTA traffic was enhanced. Results show that PSA3 is superior to its benchmark PSA2 by 12% in Mean User Throughput and 11% in Fairness. PSA2 performed the worst because it prioritizes new users and it allocated all available RBs to the scheduled user leaving the rest to wait in the buffer. PSA3 maintians good Mean User Throughput and fairnessdue to scheduling each user on its RB which leads to multi-user diversity