27 research outputs found
FPGA Implementation of a Telecommunications Trainer System
Field programmable gate arrays (FPGAs) have been used in a wide range of applications including the field of telecommunications. This paper presents the use of FPGAs in the implementation of both analog and digital modulation that includes amplitude modulation, frequency modulation, phase modulation, pulse code modulation, pulse width modulation, pulse position modulation, pulse amplitude modulation, delta modulation, amplitude shift keying, frequency shift keying, phase shift keying, time division multiplexing and different encoding techniques like non-return-to-zero line code, non-return-to-zero mark line code, non-return to zero inversion line code, Unipolar return-to-zero line code, bipolar return-to-zero line code, alternate mark inversion line code, and Manchester line code. Moreover, an FPGA can be designed to emulate a particular device like an oscilloscope, a function generator, or the like. This paper describes the capability of an FPGA to internally generate a low frequency input signal and through the use of a VGA port, it is able to display the signals in an output device. However, the use of FPGAs is not limited to the aforementioned applications because of its reconfigurability and reprogrammability
Developing an Open Database to Support Forensic Investigation of Disasters in South East Asia: FORINSEA v1.0
This article describes the development of a bespoke database, FORINSEA1.0, created to address the need for a systematic curation of information needed for the descriptive phase of the FORIN approach and its application to two study areas in the South East Asia region. FORINSEA1.0 allows researchers, for the first time, to explore and make use of subnational, geocoded data on major disasters triggered by natural hazards (flooding, earthquake, landslide and meteorological hazards) since 1945 until 2020 in the hydrological catchment of the Red River in Vietnam and the Marikina Basin in the Philippines. FORINSEA1.0 also contains relevant subnational information on relevant socio-economic policies and development of key infrastructure to provide the basis of the descriptive FORIN analysis. While the catchment approach is potentially transferable to other regions, this Data Report does not show how these records might be applied or integrated to support a FORIN investigation of a specific disaster or event, neither provide basic ground rules for setting up similar systems in other countries
Design of a Remote Real-time Groundwater Level and Water Quality Monitoring System for the Philippine Groundwater Management Plan Project
Recent technological advances allow us to utilize remote monitoring systems or real-time access of data. While the use of remote monitoring systems is not new, there are still numerous applications that can be explored and improved on, one such is groundwater level and quality monitoring. In the Philippines, the extraction of groundwater for both domestic use and industrial use are manually monitored by the government’s concerned agency and is done at least once per year. With this current setup, the real and significant state of the groundwater is not reflected in a way that is most valuable to the government and to the community. This project aims to design and develop a remote real-time groundwater level and quality monitoring system. It is intended to provide quantitative data for policy makers in addressing recurrent water shortages in the Philippines. This paper discusses the designed system composed of three modules: power module, sensors and control, and data visualization. These three modules provide real-time data from far-flung locations while being energy-sustainable. Dry runs of the system in a controlled environment yielded excellent results — average data accuracy of 96.63% for all six (6) groundwater quantity and quality parameters namely: pH, temperature, electrical conductivity, total dissolved solids, salinity, and static water level (SWL), and 90.63% data transmission reliability. Initial deployment of the system on one of the groundwater monitoring well in Metro Manila, Philippines returned a 91.16% data transmission reliability. The system is currently installed in 20 groundwater monitoring sites all-over the Philippines and is scheduled for more installations
Throughput and Power Consumption Comparisons of Zigbee-based and ISM-based Implementations of WSAN
Wireless sensor and actuator networks have expanding applications which requires better throughput, power efficiency and cost effectiveness. This study intends to contribute to the growing pool of knowledge on WSAN especially in the design for novel applications such as image or video over WSANs, and solar energy and RF energy harvesting for the WSAN nodes. Two basic scalable wireless sensor and actuator networks were implemented and characterized in terms of throughput and power consumption. The two WSANs are the Zigbee-based WSAN which is based on the IEEE 802.15.4 protocol, and the ISM-based Zigbee which makes use of the industrial, scientific and medical (ISM) radio bands. The star topology was used for both WSAN implementations. The throughput is quantified with varied factors including distance from node to node, obstructions in between nodes and cochannel interference. As distance and obstructions between nodes are increased, the throughput for both networks decreases with varying degrees. Co-channel interference is also considered. The ISM-based WSAN network is weak in dealing with co-channel interference and error rate as compared to the Zigbee-based WSAN, thus requiring it to have a better data encryption. Power consumption is generally larger for the ISM-based WSAN as compared to its Zigbee-based counterpart. However, the ISM-based nodes consume the same power even up to a few hundreds of meters distance and are thus practical for covering large distances. Therefore, the Zigbee-based WSAN system is more appropriate for closed environment, such as in room automation and home automation applications where distance from node to node is relatively shorter. The ISMbased WSAN prototype, on the other hand, can be developed further for applications in larger areas such as deployment in fields and cities, since transmission is not generally limited by distance and obstructions
Software and Data Visualization Platform for Groundwater Level and Quality Monitoring System
Rapid urbanization and increasing population come with the increased extraction and use of groundwater resources. To track the effect of these activities on groundwater level and quantity; a system for real-time monitoring is devised. In this paper; we present a software system design that enables a locally-developed groundwater level and water quality monitoring hardware setup to gather water quality parameter data; send it to a cloud server; and present organized data for better visualization. The hardware setup consists of an Arduino microcontroller. Upon deployment; the hardware setup is linked to an Android application that connects to the web-based platform
Developing an Open Database to Support Forensic Investigation of Disasters in South East Asia: FORINSEA v1.0
Short-term stochastic load forecasting using autoregressive integrated moving average models and Hidden Markov Model
Load forecasting, particularly short-term load forecasting (STLF) plays a vital role in the economy streaming and tracking of power system. Many stochastic and artificial intelligence techniques haven been used in order to come up with an accurate (less error) short-term load forecast. Here, we introduce a new approach to short-term load forecasting (STLF) using the conventional Hidden Markov Model (HMM) then compare it with Autoregressive Integrated Moving Average (ARIMA) models. Three-dimensional continuous multivariate Gaussian emission probabilities are used in this experiment for HMM. Meanwhile for ARIMA models, different parameters are used for different kinds of dataset. Comparison is done afterwards to the actual load value using MAPE and RMSE
Development and Implementation of an IoT Platform
Interconnection and management of distributed digital devices can be expensive, time consuming, involved, and difficult. The proposed solution is a well-designed IoT platform that can significantly reduce the cost, time, effort, and complexity associated with such tasks. This paper presents the development and implementation of a reconfigurable, customizable, cost-effective, modular, and lightweight IoT platform. Using HTTP requests or SMS messages, devices can easily send data to this IoT platform with minimal configuration. The IoT platform features user management, node registration and setup, data visualization, and data extraction via web UI. The platform can also be deployed on local networks. The IoT platform has also been load tested with simultaneous HTTP requests from 75 virtual machines with results giving less than 1% data loss
Design and Development of a Wireless Sensor Network Framework for Water Quality Remote Monitoring
This study involves the design and development of a wireless sensor network (WSN) that integrates several sensing modules into a fully-functional system. The overall system is composed of a remote server, a controller node, and several sensing modules. The controller node is implemented using an Android mobile phone with Bluetooth and 3G capabilities. Bluetooth is used to communicate with the various sensing modules; while 3G is used to relay data to the remote server. The sensing modules utilize an Arduino Mega 2560 (with the sensor circuits) and a Bluetooth shield. Test results show that this framework is a viable design for WSN systems and can be used for remote installations that can be continuously upgraded over time
Development of an EEG-based Brain-Controlled System for a Virtual Prosthetic Hand
Meant to improve the overall quality of life for those with physical or motor impairments, this paper explores the use of EEG and its potential in controlling a prosthetic hand. EEG signal acquisition is centered on oscillatory features through the sensory motor rhythm which can be obtained through motor-imagery (MI). The EEGNet, a convolutional neural network, is used for feature extraction and signal classification of five motor-imagery classes of a hand. A reinforced model through a transfer learning approach deemed to have the best cross-validation accuracy. A real-time debugging module for the virtual hand was implemented using MuJoCo HAPTIX