Displaying publications 1 - 20 of 116 in total

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  1. Abdul Rauf Abdul Rasam, Abdul Rauf Abdul Rasam, Azri Haziq Azlin, Noraqila Aiman Abu, Ahmad Norhisyam Idris, Nurmilah Romeyu
    Jurnal Inovasi Malaysia, 2020;3(2):87-99.
    MyJurnal
    Disability is termed as both evolving concept and manifestation of interaction between persons with disabilities (PWDs) and physical and environmental barriers that holds them back from contributing actively in a society. People who fall in this category will find themselves trapped in a such vulnerable condition as they may not be able to cope with their daily problems without high surveillance from their guardian. Development of a mobile apps and web GIS-based healthcare system in Ampang is proposed in this study as this application has a bright potential to assist PWDs in terms of accessibilities to reach healthcare centres. The main objectives of this paper are i) to study the needs assessment on the proposed system, ii) to develop a mobile and web GIS-based healthcare information system and iii) to evaluate the performance of the proposed system. Selected respondents agreed on the development of the prototype system, namely the mobile apps and web system. The system was created with main menus such as doctor home visits, ambulance and medication delivery. Medical support team can also perform analyses in the system for PWD needs such as shortest path analysis, buffering and view of the main menus.
    Matched MeSH terms: Geographic Information Systems
  2. Abdul Rauf Abdul Rasam, Noresah Mohd Shariff, Dony, Jiloris F., Saiful Aman Sulaiman
    Jurnal Inovasi Malaysia, 2018;2(1):75-88.
    MyJurnal
    An innovative health information system can be used to support the control of tuberculosis (TB) in Malaysia. The existing system of MyTB has helped in the national TB information management and decision-making process. However, the system can be further enhanced by producing a prototype of Geospatial Tuberculosis Information System (GeoTBiS). It is a geospatial decision support system that was initially proposed in Shah Alam, Selangor. Geospatial data has spatio-temporal characteristics that can be used to understand the basic elements of TB aetiology, while geospatial operations are employed to collect, manage and disseminate the data in a geographical information system (GIS) environment. The disease map and epidemiological risk analysis are produced using a global positioning system (GPS), satellite imagery, geostatistical analysis and web mapping services. This GeoTBiS has demonstrated the geospatial capabilities in enhancing the current system functions, and several recommendations towards a practicable application.
    Matched MeSH terms: Geographic Information Systems
  3. Abdullah N, Al-Wesabi OA, Mohammed BA, Al-Mekhlafi ZG, Alazmi M, Alsaffar M, et al.
    Int J Environ Res Public Health, 2022 Oct 11;19(20).
    PMID: 36293647 DOI: 10.3390/ijerph192013066
    Urban areas worldwide are in the race to become smarter, and the Kingdom of Saudi Arabia (KSA) is no exception. Many of these have envisaged a chance to establish devoted municipal access networks to assist all kinds of city administration and preserve services needing data connectivity. Organizations unanimously concentrate on sustainability issues with key features of general trends, particularly the combination of the 3Rs (reduce waste, reuse and recycle resources). This paper demonstrates how the incorporation of the Internet of Things (IoT) with data access networks, geographic information systems and combinatorial optimization can contribute to enhancing cities' administration systems. A waste-gathering approach based on supplying smart bins is introduced by using an IoT prototype embedded with sensors, which can read and convey bin volume data over the Internet. However, from another perspective, the population and residents' attitudes directly affect the control of the waste management system. The conventional waste collection system does not cover all areas in the city. It works based on a planned scheme that is implemented by the authorized organization focused on specific popular and formal areas. The conventional system cannot observe a real-time update of the bin status to recognize whether the waste level condition is 'full,' 'not full,' or 'empty.' This paper uses IoT in the container and trucks that secure the overflow and separation of waste. Waste source locations and population density influence the volume of waste generation, especially waste food, as it has the highest amount of waste generation. The open public area and the small space location problems are solved by proposing different truck sizes based on the waste type. Each container is used for one type of waste, such as food, plastic and others, and uses the optimization algorithm to calculate and find the optimal route toward the full waste container. In this work, the situations in KSA are evaluated, and relevant aspects are explored. Issues relating to the sustainability of organic waste management are conceptually analyzed. A genetic-based optimization algorithm for waste collection transportation enhances the performance of waste-gathering truck management. The selected routes based on the volume status and free spaces of the smart bins are the most effective through those obtainable towards the urgent smart bin targets. The proposed system outperforms other systems by reducing the number of locations and smart bins that have to be visited by 46% for all waste types, whereas the conventional and existing systems have to visit all locations every day, resulting in high cost and consumption time.
    Matched MeSH terms: Geographic Information Systems
  4. Abousaeidi M, Fauzi R, Muhamad R
    Saudi J Biol Sci, 2016 Sep;23(5):555-64.
    PMID: 27579003 DOI: 10.1016/j.sjbs.2015.06.004
    This study involves the adoption of the Geographic Information System (GIS) modeling approach to determine the quickest routes for fresh vegetable delivery. During transport, fresh vegetables mainly deteriorate on account of temperature and delivery time. Nonetheless, little attention has been directed to transportation issues in most areas within Kuala Lumpur. In addition, perishable food normally has a short shelf life, thus timely delivery significantly affects delivery costs. Therefore, selecting efficient routes would consequently reduce the total transportation costs. The regression model is applied in this study to determine the parameters that affect route selection with respect to the fastest delivery of fresh vegetables. For the purpose of this research, ArcGIS software with network analyst extension is adopted to solve the problem of complex networks. The final output of this research is a map of quickest routes with the best delivery times based on all variables. The variables tested from regression analysis are the most effective parameters to make the flow of road networks slower. The objective is to improve the delivery services by achieving the least drive time. The main findings of this research are that Land use such as residential area and population as variables are the effective parameters on drive time.
    Matched MeSH terms: Geographic Information Systems
  5. Abousaeidi M, Fauzi R, Muhamad R
    J Environ Biol, 2016 09;37(5 Spec No):1167-1176.
    PMID: 29989749
    Perishable products must be transported quickly from its production area to the markets due to the climatic conditions of Malaysia. Deterioration of fresh produce is affected by temperature and delivery time. The cost to achieve such timely delivery of perishable food can affect the revenue of suppliers and retailers. Choosing an efficient delivery route at right time can reduce the total transportation cost. However, insufficient attention has been given to transportation issues with regards to fresh food delivery of greater Kuala Lumpur. The present study involves adoption of the Geographic Information System (GIS) modelling approach to determine the fastest delivery routes for fresh products to several hypermarkets. For this purpose, ArcGIS software was adopted for solving the problem of a complex road networks. With a goal of realizing the shortest time for delivery route planning, impedance function would be integrated by taking into account the time emphasized in the study. The main findings of this study include determination of efficient routes for delivery of fresh vegetables based on minimal drive time. It has been proposed that the fastest route model for delivery of fresh products is based on comparing two time frames within a day. The final output of this research was a map of quickest routes with best delivery time based on two time frames.
    Matched MeSH terms: Geographic Information Systems*
  6. Aburas MM, Ahamad MSS, Omar NQ
    Environ Monit Assess, 2019 Mar 05;191(4):205.
    PMID: 30834982 DOI: 10.1007/s10661-019-7330-6
    Spatio-temporal land-use change modeling, simulation, and prediction have become one of the critical issues in the last three decades due to uncertainty, structure, flexibility, accuracy, the ability for improvement, and the capability for integration of available models. Therefore, many types of models such as dynamic, statistical, and machine learning (ML) models have been used in the geographic information system (GIS) environment to fulfill the high-performance requirements of land-use modeling. This paper provides a literature review on models for modeling, simulating, and predicting land-use change to determine the best approach that can realistically simulate land-use changes. Therefore, the general characteristics of conventional and ML models for land-use change are described, and the different techniques used in the design of these models are classified. The strengths and weaknesses of the various dynamic, statistical, and ML models are determined according to the analysis and discussion of the characteristics of these models. The results of the review confirm that ML models are the most powerful models for simulating land-use change because they can include all driving forces of land-use change in the simulation process and simulate linear and non-linear phenomena, which dynamic models and statistical models are unable to do. However, ML models also have limitations. For instance, some ML models are complex, the simulation rules cannot be changed, and it is difficult to understand how ML models work in a system. However, this can be solved via the use of programming languages such as Python, which in turn improve the simulation capabilities of the ML models.
    Matched MeSH terms: Geographic Information Systems
  7. Aburas MM, Ho YM, Ramli MF, Ash'aari ZH
    Environ Monit Assess, 2018 Feb 20;190(3):156.
    PMID: 29464400 DOI: 10.1007/s10661-018-6522-9
    The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.
    Matched MeSH terms: Geographic Information Systems
  8. Aburas, Maher Milad, Sabrina Ho Abdullah, Mohammad Firuz Ramli, Zulfa Hanan Ash'aari
    MyJurnal
    Remote sensing and geographic information system techniques are significant and popular approaches that have been used in recent years to measure and map urban growth patterns. This paper primarily aims to provide a basis for a literature review of urban growth measurement and mapping by using different methods. For this purpose, the general characteristics of measuring and mapping urban growth patterns are described and classified. The strengths and weaknesses of the various methods have been identified from an analysis and discussion of the characteristics of the techniques. Results of reviews confirm that combining quantitative and qualitative techniques, such as Shannon approach and change detection, to measure and map urban growth patterns will improve understanding of the phenomenon of urban growth. Moreover, using social and economic data such as population and income data will improve understanding of the relationships between causes and effects. The integration of social and economic factors with quantitative and qualitative techniques will contribute to a perfect evaluation of urban growth patterns and land use changes, taking technical, social, economic, spatial, and temporal factors into account.
    Matched MeSH terms: Geographic Information Systems
  9. Adnan AI, Hanapi ZM, Othman M, Zukarnain ZA
    PLoS One, 2017;12(1):e0170273.
    PMID: 28121992 DOI: 10.1371/journal.pone.0170273
    Due to the lack of dependency for routing initiation and an inadequate allocated sextant on responding messages, the secure geographic routing protocols for Wireless Sensor Networks (WSNs) have attracted considerable attention. However, the existing protocols are more likely to drop packets when legitimate nodes fail to respond to the routing initiation messages while attackers in the allocated sextant manage to respond. Furthermore, these protocols are designed with inefficient collection window and inadequate verification criteria which may lead to a high number of attacker selections. To prevent the failure to find an appropriate relay node and undesirable packet retransmission, this paper presents Secure Region-Based Geographic Routing Protocol (SRBGR) to increase the probability of selecting the appropriate relay node. By extending the allocated sextant and applying different message contention priorities more legitimate nodes can be admitted in the routing process. Moreover, the paper also proposed the bound collection window for a sufficient collection time and verification cost for both attacker identification and isolation. Extensive simulation experiments have been performed to evaluate the performance of the proposed protocol in comparison with other existing protocols. The results demonstrate that SRBGR increases network performance in terms of the packet delivery ratio and isolates attacks such as Sybil and Black hole.
    Matched MeSH terms: Geographic Information Systems/economics
  10. Ahmad Kamal N, Muhammad NS, Abdullah J
    Environ Pollut, 2020 Apr;259:113909.
    PMID: 31927277 DOI: 10.1016/j.envpol.2020.113909
    Malaysia is a tropical country that is highly dependent on surface water for its raw water supply. Unfortunately, surface water is vulnerable to pollution, especially in developed and dense urban catchments. Therefore, in this study, a methodology was developed for an extensive temporal water quality index (WQI) and classification analysis, simulations of various pollutant discharge scenarios using QUAL2K software, and maps with NH3-N as the core pollutant using an integrated QUAL2K-GIS. It was found that most of the water quality stations are categorized as Class III (slightly polluted to polluted). These stations are surrounded by residential areas, industries, workshops, restaurants and wet markets that contribute to the poor water quality levels. Additionally, low WQI values were reported in 2010 owing to development and agricultural activities. However, the WQI values improved during the wet season. High concentrations of NH3-N were found in the basin, especially during dry weather conditions. Three scenarios were simulated, i.e. 10%, 50% and 70% of pollution discharge into Skudai river using a calibrated and validated QUAL2K model. Model performance was evaluated using the relative percentage difference. An inclusive graph showing the current conditions and pollution reduction scenarios with respect to the distance of Skudai river and its tributaries is developed to determine the WQI classification. Comprehensive water quality maps based on NH3-N as the core pollutant are developed using integrated QUAL2K-GIS to illustrate the overall condition of the Skudai river. High NH3-N in the Skudai River affects water treatment plant operations. Pollution control of more than 90% is required to improve the water quality classification to Class II. The methodology and analysis developed in this study can assist various stakeholders and authorities in identifying problematic areas and determining the required percentage of pollution reduction to improve the Skudai River water quality.
    Matched MeSH terms: Geographic Information Systems
  11. Ahmad SZ, Ahamad MS, Yusoff MS
    Waste Manag Res, 2014 Jan;32(1):24-33.
    PMID: 24241167 DOI: 10.1177/0734242X13507313
    Proper implementation of landfill siting with the right regulations and constraints can prevent undesirable long-term effects. Different countries have respective guidelines on criteria for new landfill sites. In this article, we perform a comparative study of municipal solid waste landfill siting criteria stated in the policies and guidelines of eight different constitutional bodies from Malaysia, Australia, India, U.S.A., Europe, China and the Middle East, and the World Bank. Subsequently, a geographic information system (GIS) multi-criteria evaluation model was applied to determine new suitable landfill sites using different criterion parameters using a constraint mapping technique and weighted linear combination. Application of Macro Modeler provided in the GIS-IDRISI Andes software helps in building and executing multi-step models. In addition, the analytic hierarchy process technique was included to determine the criterion weight of the decision maker's preferences as part of the weighted linear combination procedure. The differences in spatial results of suitable sites obtained signifies that dissimilarity in guideline specifications and requirements will have an effect on the decision-making process.
    Matched MeSH terms: Geographic Information Systems
  12. Ahmed AA, Pradhan B
    Environ Monit Assess, 2019 Feb 26;191(3):190.
    PMID: 30809746 DOI: 10.1007/s10661-019-7333-3
    This study proposes a neural network (NN) model to predict and simulate the propagation of vehicular traffic noise in a dense residential area at the New Klang Valley Expressway (NKVE) in Shah Alam, Malaysia. The proposed model comprises of two main simulation steps: that is, the prediction of vehicular traffic noise using NN and the simulation of the propagation of traffic noise emission using a mathematical model. First, the NN model was developed with the following selected noise predictors: the number of motorbikes, the sum of vehicles, car ratio, heavy vehicle ratio (e.g. truck, lorry and bus), highway density and a light detection and ranging (LiDAR)-derived digital surface model (DSM). Subsequently, NN and its hyperparameters were optimised by a systematic optimisation procedure based on a grid search approach. The noise propagation model was then developed in a geographic information system (GIS) using five variables, namely road geometry, barriers, distance, interaction of air particles and weather parameters. The noise measurement was conducted continuously at 15-min intervals and the data were analysed by taking the minimum, maximum and average values recorded during the day. The measurement was performed four times a day (i.e. morning, afternoon, evening, and midnight) over two days of the week (i.e. Sunday and Monday). An optimal radial basis function NN was used with 17 hidden layers. The learning rate and momentum values were 0.05 and 0.9, respectively. Finally, the accuracy of the proposed method achieved 78.4% with less than 4.02 dB (A) error in noise prediction. Overall, the proposed models were found to be promising tools for traffic noise assessment in dense urban areas.
    Matched MeSH terms: Geographic Information Systems
  13. Ahmed JB, Salisu A, Pradhan B, Alamri AM
    Insects, 2020 Oct 24;11(11).
    PMID: 33114307 DOI: 10.3390/insects11110728
    Termite nests have long been suggested to be good indicators of groundwater but only a few studies are available to demonstrate the relationship between the two. This study therefore aims at investigating the most favourable spots for locating groundwater structures on a small parcel of land with conspicuous termite activity. To achieve this, geophysical soundings using the renowned vertical electrical sounding (VES) technique was carried out on the gridded study area. A total of nine VESs with one at the foot of a termitarium were conducted. The VES results were interpreted and assessed via two different techniques: (1) physical evaluation as performed by drillers in the field and (2) integration of primary and secondary geoelectrical parameters in a geographic information system (GIS). The result of the physical evaluation indicated a clear case of subjectivity in the interpretation but was consistent with the choice of VES points 1 and 6 (termitarium location) as being the most prospective points to be considered for drilling. Similarly, the integration of the geoelectrical parameters led to the mapping of the most prospective groundwater portion of the study area with the termitarium chiefly in the center of the most suitable region. This shows that termitaria are valuable landscape features that can be employed as biomarkers in the search of groundwater.
    Matched MeSH terms: Geographic Information Systems
  14. Ahsan MR, Islam MT, Habib Ullah M, Mahadi WN, Latef TA
    ScientificWorldJournal, 2014;2014:909854.
    PMID: 25165750 DOI: 10.1155/2014/909854
    This paper presents a compact sized inset-fed rectangular microstrip patch antenna embedded with double-P slots. The proposed antenna has been designed and fabricated on ceramic-PTFE composite material substrate of high dielectric constant value. The measurement results from the fabricated prototype of the antenna show -10 dB reflection coefficient bandwidths of 200 MHz and 300 MHz with center resonant frequency of 1.5 GHz and 4 GHz, respectively. The fabricated antenna has attained gains of 3.52 dBi with 81% radiation efficiency and 5.72 dBi with 87% radiation efficiency for lower band and upper band, respectively. The measured E- and H-plane radiation patterns are also presented for better understanding. Good agreement between the simulation and measurement results and consistent radiation patterns make the proposed antenna suitable for GPS and C-band applications.
    Matched MeSH terms: Geographic Information Systems/instrumentation*
  15. Al-Abadi AM, Pradhan B, Shahid S
    Environ Monit Assess, 2015 Oct;188(10):549.
    PMID: 27600115 DOI: 10.1007/s10661-016-5564-0
    The objective of this study is to delineate groundwater flowing well zone potential in An-Najif Province of Iraq in a data-driven evidential belief function model developed in a geographical information system (GIS) environment. An inventory map of 68 groundwater flowing wells was prepared through field survey. Seventy percent or 43 wells were used for training the evidential belief functions model and the reset 30 % or 19 wells were used for validation of the model. Seven groundwater conditioning factors mostly derived from RS were used, namely elevation, slope angle, curvature, topographic wetness index, stream power index, lithological units, and distance to the Euphrates River in this study. The relationship between training flowing well locations and the conditioning factors were investigated using evidential belief functions technique in a GIS environment. The integrated belief values were classified into five categories using natural break classification scheme to predict spatial zoning of groundwater flowing well, namely very low (0.17-0.34), low (0.34-0.46), moderate (0.46-0.58), high (0.58-0.80), and very high (0.80-0.99). The results show that very low and low zones cover 72 % (19,282 km(2)) of the study area mostly clustered in the central part, the moderate zone concentrated in the west part covers 13 % (3481 km(2)), and the high and very high zones extended over the northern part cover 15 % (3977 km(2)) of the study area. The vast spatial extension of very low and low zones indicates that groundwater flowing wells potential in the study area is low. The performance of the evidential belief functions spatial model was validated using the receiver operating characteristic curve. A success rate of 0.95 and a prediction rate of 0.94 were estimated from the area under relative operating characteristics curves, which indicate that the developed model has excellent capability to predict groundwater flowing well zones. The produced map of groundwater flowing well zones could be used to identify new wells and manage groundwater storage in a sustainable manner.
    Matched MeSH terms: Geographic Information Systems
  16. Al-Mashreki MH, Akhir JB, Abd Rahim S, Desa KM, Rahman ZA
    Pak J Biol Sci, 2010 Dec 01;13(23):1116-28.
    PMID: 21313888
    In the present study, an assessment of land suitability potential for agriculture in the study area of IBB governorate, Republic of Yemen has been conducted through close examination of the indicators of land characteristics and qualities. The objective of this study is to evaluate the available land resource and produce the potential map of the study area. Remote sensing data help in mapping land resources, especially in mountainous areas where accessibility is limited. Satellite imagery data used for this study includes data from multi-temporal Landsat TM which dated June 2001. The parameters taken into consideration were 16 thematic maps i.e., slope, DEM, rainfall, soil, land use, land degradation as well as land characteristics maps. Satellite image of the study area has been classified for land use, land degradation and soil maps preparation, while topo sheet and ancillary data have been used for slope and DEM maps and soil properties determination. The land potential of the study area was categorized as very high, high, moderate, low and very low by adopting the logical criteria. These categories were arrived at by integrating the various layers with corresponding weights in a Geographical Information System (GIS). The study demonstrates that the study area can be categorized into spatially distributed agriculture potential zones based on the soil properties, terrain characteristics and analyzing present land use. This approach has the potential as a useful tool for guiding policy decision on sustainable land resource management.
    Matched MeSH terms: Geographic Information Systems*
  17. Alam MJ, Ahamed E, Faruque MRI, Islam MT, Tamim AM
    PLoS One, 2019;14(11):e0224478.
    PMID: 31714917 DOI: 10.1371/journal.pone.0224478
    Interferences and accuracy problem are one of the most talked issues in today's world for sensor technology. To deal with this contention, a microstrip framework consisting of a dual mode double negative (DNG) metamaterial based bandpass filter is presented in this article. To obtain the ultimate noise reduction bandpass filter, the proposed structure has to go through a series of development process, where the characteristics of the structure are tested to the limit. This filter is built on Rogers RT-5880 substrate with a 50Ω microstrip line. To pursue the elementary mode of resonant frequency, the ground layer of the structure is kept partially filled and a gradual analysis is executed on the prospective metamaterial (resonator) unit cell. Depending on the developed unit cell, the filter is constructed and fabricated to verify the concept, concentrating on GPS (1.55GHz), Earth Exploration-Satellite (2.70GHz) and WiMAX (3.60GHz) bands of frequencies. Moreover, the structure is investigated using Nicolson-Ross-Weir (NRW) approach to justify the metamaterial characteristics, and also tested on S-parameters, current distribution, electric and magnetic fields and quality factor. Having a propitious architecture and DNG characteristics, the proposed structure is suitable for bandpass filter for GPS, Earth Exploration-Satellite and WiMAX frequency sensing applications.
    Matched MeSH terms: Geographic Information Systems*
  18. Alshami IH, Ahmad NA, Sahibuddin S, Firdaus F
    Sensors (Basel), 2017 Aug 05;17(8).
    PMID: 28783047 DOI: 10.3390/s17081789
    The Global Positioning System demonstrates the significance of Location Based Services but it cannot be used indoors due to the lack of line of sight between satellites and receivers. Indoor Positioning Systems are needed to provide indoor Location Based Services. Wireless LAN fingerprints are one of the best choices for Indoor Positioning Systems because of their low cost, and high accuracy, however they have many drawbacks: creating radio maps is time consuming, the radio maps will become outdated with any environmental change, different mobile devices read the received signal strength (RSS) differently, and peoples' presence in LOS between access points and mobile device affects the RSS. This research proposes a new Adaptive Indoor Positioning System model (called DIPS) based on: a dynamic radio map generator, RSS certainty technique and peoples' presence effect integration for dynamic and multi-floor environments. Dynamic in our context refers to the effects of people and device heterogeneity. DIPS can achieve 98% and 92% positioning accuracy for floor and room positioning, and it achieves 1.2 m for point positioning error. RSS certainty enhanced the positioning accuracy for floor and room for different mobile devices by 11% and 9%. Then by considering the peoples' presence effect, the error is reduced by 0.2 m. In comparison with other works, DIPS achieves better positioning without extra devices.
    Matched MeSH terms: Geographic Information Systems
  19. Amin MS, Reaz MB, Nasir SS, Bhuiyan MA, Ali MA
    ScientificWorldJournal, 2014;2014:597180.
    PMID: 25276855 DOI: 10.1155/2014/597180
    Precise navigation is a vital need for many modern vehicular applications. The global positioning system (GPS) cannot provide continuous navigation information in urban areas. The widely used inertial navigation system (INS) can provide full vehicle state at high rates. However, the accuracy diverges quickly in low cost microelectromechanical systems (MEMS) based INS due to bias, drift, noise, and other errors. These errors can be corrected in a stationary state. But detecting stationary state is a challenging task. A novel stationary state detection technique from the variation of acceleration, heading, and pitch and roll of an attitude heading reference system (AHRS) built from the inertial measurement unit (IMU) sensors is proposed. Besides, the map matching (MM) algorithm detects the intersections where the vehicle is likely to stop. Combining these two results, the stationary state is detected with a smaller timing window of 3 s. A longer timing window of 5 s is used when the stationary state is detected only from the AHRS. The experimental results show that the stationary state is correctly identified and the position error is reduced to 90% and outperforms previously reported work. The proposed algorithm would help to reduce INS errors and enhance the performance of the navigation system.
    Matched MeSH terms: Geographic Information Systems/standards*
  20. Arebey M, Hannan MA, Basri H, Begum RA, Abdullah H
    Environ Monit Assess, 2011 Jun;177(1-4):399-408.
    PMID: 20703798 DOI: 10.1007/s10661-010-1642-x
    The integration of communication technologies such as radio frequency identification (RFID), global positioning system (GPS), general packet radio system (GPRS), and geographic information system (GIS) with a camera are constructed for solid waste monitoring system. The aim is to improve the way of responding to customer's inquiry and emergency cases and estimate the solid waste amount without any involvement of the truck driver. The proposed system consists of RFID tag mounted on the bin, RFID reader as in truck, GPRS/GSM as web server, and GIS as map server, database server, and control server. The tracking devices mounted in the trucks collect location information in real time via the GPS. This information is transferred continuously through GPRS to a central database. The users are able to view the current location of each truck in the collection stage via a web-based application and thereby manage the fleet. The trucks positions and trash bin information are displayed on a digital map, which is made available by a map server. Thus, the solid waste of the bin and the truck are being monitored using the developed system.
    Matched MeSH terms: Geographic Information Systems
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