International Journal of Reconfigurable and Embedded Systems (IJRES)
The centre of gravity of the computer industry is now moving from personal computing into embedded computing with the advent of VLSI system level integration and reconfigurable core in system-on-chip (SoC). Reconfigurable and Embedded systems are increasingly becoming a key technological component of all kinds of complex technical systems, ranging from audio-video-equipment, telephones, vehicles, toys, aircraft, medical diagnostics, pacemakers, climate control systems, manufacturing systems, intelligent power systems, security systems, to weapons etc. The aim of IJRES is to provide a vehicle for academics, industrial professionals, educators and policy makers working in the field to contribute and disseminate innovative and important new work on reconfigurable and embedded systems. The scope of the IJRES addresses the state of the art of all aspects of reconfigurable and embedded computing systems with emphasis on algorithms, circuits, systems, models, compilers, architectures, tools, design methodologies, test and applications.
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<![CDATA[Internet based highly secure data transmission system in health care monitoring system ]]>
<![CDATA[Ram, Gubbala Bhaskar Phani]]>;
<![CDATA[Thirunarayanan, Shankar]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp681-686
<![CDATA[The health care systems in our contemporary countries are advancing rapidly in terms of maturity and professionalism. In an effort to alleviate the current burden on the public health system and boost the popularity of regular health self-checks, this method has been developed for producing prediagnoses that are easier to use, quicker, and more accurate. To ascertain how well the heart is circulating oxygen throughout the body, a pulse test, a painless examination that measures an individual's degree of oxygen saturation, is used. It can be used to evaluate the state of any patient with a disease, particularly those with pulmonary problems. Diseases in these patients could need ongoing observation and care. Our system comes to the rescue in order to resolve this problem. This portable system is simple to use and may be taken anywhere by the subject. The internet of things (IoT) will update the pertinent parameters. This health monitoring system's controller is made up of an adaptor, a saturation of peripheral oxygen (SPO2) sensor (a blood oxygen meter), a temperature sensor, a heart rate sensor, a WiFi module, and a liquid crystal display (LCD).]]>
<![CDATA[Earthquake magnitude prediction in Indonesia using a supervised method based on cloud radon data ]]>
<![CDATA[Pratama, Thomas Oka]]>;
<![CDATA[Sunarno, Sunarno]]>;
<![CDATA[Wijatna, Agus Budhie]]>;
<![CDATA[Haryono, Eko]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp577-585
<![CDATA[In the challenging realm of earthquake prediction, the reliability of forecasting systems has remained a persistent obstacle. This study focuses on earthquake magnitude prediction in Indonesia, leveraging supervised machine learning techniques and cloud radon data. We present an analysis of the tele-monitoring system, data collection methods, and the application of regression-based machine learning algorithms. Utilizing a comprehensive dataset spanning 30 training instances and 105 test instances, the study evaluates multiple metrics to ascertain the efficacy of the prediction models. Our findings reveal that the linear regression approach yields the best earthquake magnitude prediction method, with the lowest values across multiple evaluation metrics: standard deviation 0.40, mean absolute error (MAE) 0.30, mean absolute percentage error (MAPE) 6%, root mean square error (RMSE) 0.52, mean squared error (MSE) 0.28, symmetric mean absolute percentage error (SMAPE) 0.06, and conformal normalized mean absolute percentage error (cnSMAPE) 0.97. Additionally, we discuss the implications of the research results and the potential applications in enhancing existing earthquake prediction methodologies.]]>
<![CDATA[Smart farming based on IoT to predict conditions using machine learning ]]>
<![CDATA[Widianto, Mochammad Haldi]]>;
<![CDATA[Setiawan, Yovanka Davincy]]>;
<![CDATA[Ghilchrist, Bryan]]>;
<![CDATA[Giovan, Gerry]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp595-603
<![CDATA[Smart farming is a type of technology that utilizes the internet of things (IoT) to provide information on agricultural and environmental conditions as well as perform automation. Some of these ecological conditions can be used and analyzed in machine learning (ML) data management. This study focuses on utilizing ML algorithms to find the best prediction; typically used methods include linear regression, decision tree (DT), random forest (RF), and extreme gradient boosting (XGBoost). In the application of smart farming, research on IoT and artificial intelligence (AI) is still uncommon since most IoT cannot make predictions like AI. Because basically, some IoT can't make predictions as AI does. In this Study, predictions were made by looking at the regression results in the form of root mean square error (RMSE) and absolute error. The results show a strong and weak correlation between features (positive or negative). The best prediction results are obtained by XGBoost when predicting temperature (RMSE 6.656 and absolute error 3.948) and (soil moisture 17.151 and absolute error 11.269). However, using different parameters (RMSE RF and absolute error DT) on RF and DT resulted in good and distinct results. Linear regression, on the other hand, produced unsatisfactory and poor result.]]>
<![CDATA[Portable neonatus incubator based on global positioning system ]]>
<![CDATA[Salahuddin, Nur Sultan]]>;
<![CDATA[Sari, Sri Peornomo]]>;
<![CDATA[Musyaffa, Aqilla Rahman]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp735-747
<![CDATA[The role of baby incubator is crucial in assisting premature babies to adjust to their new surroundings. However, the current baby incubator causes challenges when used for emergency first aid. The challenge is often because of its cumbersome size, which makes transportation to referral hospitals difficult. To address this issue, portable neonate incubator based on the global positioning system (GPS) was developed. The results of implementation testing showed that the incubator system effectively monitored longitude and latitude coordinates, as well as the temperature and humidity of the incubator room, and the body temperature of neonates. Weighing approximately 5.8 kg, this incubator was versatile, compatible with both AC and DC voltage power sources, and came equipped with a carrying bag for easy transportation by midwives or medical personnel. Consequently, this development marked an innovative advancement in neonate incubator medical equipment, facilitating the swift tracking of the neonate incubator's coordinate position in case of unexpected events on the way to the hospital.]]>
<![CDATA[Internet of things and long range-based bridge slope early detection systems ]]>
<![CDATA[Umar, Nuraeni]]>;
<![CDATA[Syarif, Syafruddin]]>;
<![CDATA[Dewiani, Dewiani]]>;
<![CDATA[Baharuddin, Merna]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp674-680
<![CDATA[This research proposes an internet of things and long range (LoRa)-based bridge slope status monitoring and warning system that is wireless, low-cost, and user-friendly, with continuous data sent. Bridge inspection officers can easily obtain bridge slope data via a web browser on a cell phone. The design uses Arduino integrated development environment software and an ITGMPU accelerometer sensors, TTGO ESP32, cellphones, successfully identified tilt angle variations from 0.11° to 15.2° were the research's outputs, and and they were continuously transmitted to the bridge inspection officer's mobile phone. Measurements of throughput, quality of service (QoS), and latency characteristics have been made to assess the internet network's performance. The network system performance statistics show an average measured network delay of 1.2 seconds, a throughput of 85 bps, and a QoS of 0%. Consequently, the system performs well and the internet network performance falls into the very good range.]]>
<![CDATA[Leveraging the learning focal point algorithm for emotional intelligence ]]>
<![CDATA[Mansour, Salah Eddine]]>;
<![CDATA[Sakhi, Abdelhak]]>;
<![CDATA[Kzaz, Larbi]]>;
<![CDATA[Sekkaki, Abderrahim]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp767-773
<![CDATA[One of the secrets of the success of the education process is taking into account the learner’s feelings. That is, the teacher must be characterized by high emotional intelligence (EI) to understand the student’s feelings in order to facilitate the indoctrination process for him. Within the framework of the project to create a robot teacher, we had to add this feature because of its importance. In this article, we create a computer application that classifies students' emotions based on deep learning and learning focal point (LFP) algorithm by analyzing facial expressions. That is, the robot will be able to know whether the student is happy, excited, or sad in order to deal with him appropriately.]]>
<![CDATA[Design of a linear motor-based magnetic levitation train prototype ]]>
<![CDATA[Mohd Zaidi, Muhammad Syafiq]]>;
<![CDATA[Mohd Hassan, Siti Lailatul]]>;
<![CDATA[Abdul Halim, Ili Shairah]]>;
<![CDATA[Sulaiman, Nasri]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp560-567
<![CDATA[This study explores the modelling of a magnetic levitation train and its implementation using a microcontroller. Magnetic levitation (maglev) is a technology that enables vehicles to levitate and move without wheels. Maglev research has been conducted globally, but maglev trains haven't received much attention. Due to the sophisticated linear motor technology for contactless transit, building a maglev train requires enormous investments. This paper is crucial for understanding the linear motor technologies necessary for levitation and propulsion. The primary objectives of this study include creating a model of the maglev train using a linear motor circuit, investigating the maglev effect concerning different coil and magnet types, and monitoring the train's propulsion and levitation using a microcontroller. This work constructs a linear motor system for the maglev train, comprising a mechanical structure with a permanent magnet for levitation and electromagnets for propulsion. A microcontroller is employed to sense the magnetic field, produced by the permanent magnet and electromagnets. In summary, this paper successfully designed a maglev train prototype using a linear motor circuit to establish the repulsive mechanism for both levitation and propulsion, with levitation~1 cm from the track and demonstrated the ability to move along a 30 cm track.]]>
<![CDATA[Air quality monitoring system based on low power wide area network technology at public transport stops ]]>
<![CDATA[Yauri, Ricardo]]>;
<![CDATA[Loayza, Bill]]>;
<![CDATA[Yauri, Alvaro]]>;
<![CDATA[Aquino, Anyela]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp699-707
<![CDATA[Mass migration from rural areas to urban areas has caused problems of traffic congestion, high industrial concentration and inequity in the distribution of housing in the world's capitals, generating a significant threat to sustainable development and public health due to air pollution air. In the Peruvian context, the importance of real-time monitoring of air quality is highlighted according to the standards established by the government. Several studies propose real-time environmental monitoring systems using internet of thing (IoT) technologies, electrochemical and optical sensors to measure pollutants, highlighting the need for data analysis. The objective of the paper is to show the implementation of IoT devices called sensor nodes, with long range wide area network (LoRaWAN) transmission technology for continuous monitoring of polluting gas concentrations. In addition, they are integrated into a central node called gateway to perform real-time monitoring through a web application. As an initial result, IoT devices demonstrated their effectiveness for real-time monitoring. Despite being a prototype-level result, the next stage involves its deployment at public transport stops in Lima. Overcoming the limitations of the solution, this paper establishes the foundation for future research on pollution and public health.]]>
<![CDATA[Moving objects detection based on histogram of oriented gradient algorithm chip for hazy environment ]]>
<![CDATA[Sharma, Monika]]>;
<![CDATA[Kaswan, Kuldeep Singh]]>;
<![CDATA[Yadav, Dileep Kumar]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp604-615
<![CDATA[The most important aspects of computer vision are moving object detection (MOD) and tracking. Many signal-processing applications use regional image statistics. Compute-intensive video and image processing with low latency and high throughput is done with field programmable gate array (FPGA) image processing. Local image statistics are used for edge identification and filtering. The histogram of oriented gradients (HoG) algorithm extracts local shape characteristics by equalizing histograms. The objective of the work is to design the hardware chip of the algorithm and perform the simulation in the Xilinx ISE 14.7 simulation environment. The performance of the chip is evaluated in Modelsim 10.0 simulation software to check its feasibility. The performance of the chip design is estimated on Viretx-5 FPGA and compared with the MATLAB-2020 image processing tool-based response time. This form of tracking typically deals with identifying, anchoring, and tracking images and videos. A mask made from a cut-out of the object can then determine the plane's coordinates depending on its position. This type of object tracking is frequently utilized in the field of augmented reality (AR). The algorithm is most suited for object detection using hardware controllers in haze and foggy environments.]]>
<![CDATA[Approximate single precision floating point adder for low power applications ]]>
<![CDATA[Narayanappa, Manjula]]>;
<![CDATA[Yellampalli, Siva Sankar]]>
<![CDATA[ International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijres.v13.i3.pp650-664
<![CDATA[With an increasing demand for power-hungry data-intensive computing, design methodologies with low power consumption are increasingly gaining prominence in the industry. Most of the systems operate on critical and noncritical data both. An attempt to generate a precision result results in excessive power consumption and results in a slower system. For noncritical data, approximate computing circuits significantly reduce the circuit complexity and hence power consumption. In this paper, a novel approximate single precision floating point adder is proposed with an approximate mantissa adder. The mantissa adder is designed with three 8-bit full adder blocks. In this paper, a detailed mathematical background, and proposed design approach in terms of the circuit configuration and truth tables are discussed. Additionally, a concept of switching between exact computing and approximate computing is analysed considering an approximate carry look-ahead adder. The delay and power consumption for the exact operating mode and approximate operation mode considering varied window sizes is observed. Performance of the approximate computation is compared against exact computation and varied approximate computing approaches.]]>
