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Fulltext A Distributed Testbed for 5G Scenarios: An Experimental Study

Chamran MK, Yau KA, Noor RMD, Wong R

Sensors (Basel), 2019 Dec 19;20(1).
PMID: 31861500 DOI: 10.3390/s20010018

This paper demonstrates the use of Universal Software Radio Peripheral (USRP), together with Raspberry Pi3 B+ (RP3) as the brain (or the decision making engine), to develop a distributed wireless network in which nodes can communicate with other nodes independently and make decision autonomously. In other words, each USRP node (i.e., sensor) is embedded with separate processing units (i.e., RP3), which has not been investigated in the literature, so that each node can make independent decisions in a distributed manner. The proposed testbed in this paper is compared with the traditional distributed testbed, which has been widely used in the literature. In the traditional distributed testbed, there is a single processing unit (i.e., a personal computer) that makes decisions in a centralized manner, and each node (i.e., USRP) is connected to the processing unit via a switch. The single processing unit exchanges control messages with nodes via the switch, while the nodes exchange data packets among themselves using a wireless medium in a distributed manner. The main disadvantage of the traditional testbed is that, despite the network being distributed in nature, decisions are made in a centralized manner. Hence, the response delay of the control message exchange is always neglected. The use of such testbed is mainly due to the limited hardware and monetary cost to acquire a separate processing unit for each node. The experiment in our testbed has shown the increase of end-to-end delay and decrease of packet delivery ratio due to software and hardware delays. The observed multihop transmission is performed using device-to-device (D2D) communication, which has been enabled in 5G. Therefore, nodes can either communicate with other nodes via: (a) a direct communication with the base station at the macrocell, which helps to improve network performance; or (b) D2D that improve spectrum efficiency, whereby traffic is offloaded from macrocell to small cells. Our testbed is the first of its kind in this scale, and it uses RP3 as the distributed decision-making engine incorporated into the USRP/GNU radio platform. This work provides an insight to the development of a 5G network.

Matched MeSH terms: Computers; Microcomputers
Fulltext A Review on Computer Aided Diagnosis of Acute Brain Stroke

Inamdar MA, Raghavendra U, Gudigar A, Chakole Y, Hegde A, Menon GR, et al.

Sensors (Basel), 2021 Dec 20;21(24).
PMID: 34960599 DOI: 10.3390/s21248507

Amongst the most common causes of death globally, stroke is one of top three affecting over 100 million people worldwide annually. There are two classes of stroke, namely ischemic stroke (due to impairment of blood supply, accounting for ~70% of all strokes) and hemorrhagic stroke (due to bleeding), both of which can result, if untreated, in permanently damaged brain tissue. The discovery that the affected brain tissue (i.e., 'ischemic penumbra') can be salvaged from permanent damage and the bourgeoning growth in computer aided diagnosis has led to major advances in stroke management. Abiding to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, we have surveyed a total of 177 research papers published between 2010 and 2021 to highlight the current status and challenges faced by computer aided diagnosis (CAD), machine learning (ML) and deep learning (DL) based techniques for CT and MRI as prime modalities for stroke detection and lesion region segmentation. This work concludes by showcasing the current requirement of this domain, the preferred modality, and prospective research areas.

Matched MeSH terms: Computers
Fulltext A Survey of Automatic Facial Micro-Expression Analysis: Databases, Methods, and Challenges

Oh YH, See J, Le Ngo AC, Phan RC, Baskaran VM

Front Psychol, 2018;9:1128.
PMID: 30042706 DOI: 10.3389/fpsyg.2018.01128

Over the last few years, automatic facial micro-expression analysis has garnered increasing attention from experts across different disciplines because of its potential applications in various fields such as clinical diagnosis, forensic investigation and security systems. Advances in computer algorithms and video acquisition technology have rendered machine analysis of facial micro-expressions possible today, in contrast to decades ago when it was primarily the domain of psychiatrists where analysis was largely manual. Indeed, although the study of facial micro-expressions is a well-established field in psychology, it is still relatively new from the computational perspective with many interesting problems. In this survey, we present a comprehensive review of state-of-the-art databases and methods for micro-expressions spotting and recognition. Individual stages involved in the automation of these tasks are also described and reviewed at length. In addition, we also deliberate on the challenges and future directions in this growing field of automatic facial micro-expression analysis.

Matched MeSH terms: Computers
Fulltext A Vision-Based Machine Learning Method for Barrier Access Control Using Vehicle License Plate Authentication

Islam KT, Raj RG, Shamsul Islam SM, Wijewickrema S, Hossain MS, Razmovski T, et al.

Sensors (Basel), 2020 Jun 24;20(12).
PMID: 32599883 DOI: 10.3390/s20123578

Automatic vehicle license plate recognition is an essential part of intelligent vehicle access control and monitoring systems. With the increasing number of vehicles, it is important that an effective real-time system for automated license plate recognition is developed. Computer vision techniques are typically used for this task. However, it remains a challenging problem, as both high accuracy and low processing time are required in such a system. Here, we propose a method for license plate recognition that seeks to find a balance between these two requirements. The proposed method consists of two stages: detection and recognition. In the detection stage, the image is processed so that a region of interest is identified. In the recognition stage, features are extracted from the region of interest using the histogram of oriented gradients method. These features are then used to train an artificial neural network to identify characters in the license plate. Experimental results show that the proposed method achieves a high level of accuracy as well as low processing time when compared to existing methods, indicating that it is suitable for real-time applications.

Matched MeSH terms: Computers
A case study evaluation of a Critical Care Information System adoption using the socio-technical and fit approach

Yusof MM

Int J Med Inform, 2015 Jul;84(7):486-99.
PMID: 25881560 DOI: 10.1016/j.ijmedinf.2015.03.001

Clinical information systems have long been used in intensive care units but reports on their adoption and benefits are limited. This study evaluated a Critical Care Information System implementation.

Matched MeSH terms: Attitude to Computers*
A computational method for reliable gait event detection and abnormality detection for feedback in rehabilitation

Senanayake C, Senanayake SM

Comput Methods Biomech Biomed Engin, 2011 Oct;14(10):863-74.
PMID: 20924859 DOI: 10.1080/10255842.2010.499866

In this paper, a gait event detection algorithm is presented that uses computer intelligence (fuzzy logic) to identify seven gait phases in walking gait. Two inertial measurement units and four force-sensitive resistors were used to obtain knee angle and foot pressure patterns, respectively. Fuzzy logic is used to address the complexity in distinguishing gait phases based on discrete events. A novel application of the seven-dimensional vector analysis method to estimate the amount of abnormalities detected was also investigated based on the two gait parameters. Experiments were carried out to validate the application of the two proposed algorithms to provide accurate feedback in rehabilitation. The algorithm responses were tested for two cases, normal and abnormal gait. The large amount of data required for reliable gait-phase detection necessitate the utilisation of computer methods to store and manage the data. Therefore, a database management system and an interactive graphical user interface were developed for the utilisation of the overall system in a clinical environment.

Matched MeSH terms: Computers
Fulltext A computer program for oesophago-gastro-duodenoscopy records

Paramarajah S

Singapore Med J, 1986 Apr;27(2):114-9.
PMID: 3489292

The feasibility of using a computer database management system based on an 8·bit microcomputer for storing, retrieving and analysing patient data in a limited setting (oesophago·gastro-duodenoscopy records from a peripheral general surgical department over a 1 year period) is presented. A program developed by the author was used to enter the relevant records of 208 patients undergoing the above examination, and to retrieve and analyse any desired data. Compatible statistical and graphics software packages can be used to access and analyse the data and display or print out the results. The limitations and scope for further expansion of the system are discussed.

Matched MeSH terms: Computers*; Microcomputers*
Fulltext A cybertaxonomic revision of the micro-landsnail genus Plectostoma Adam (Mollusca, Caenogastropoda, Diplommatinidae), from Peninsular Malaysia, Sumatra and Indochina

Liew TS, Vermeulen JJ, Marzuki ME, Schilthuizen M

Zookeys, 2014.
PMID: 24715783 DOI: 10.3897/zookeys.393.6717

Plectostoma is a micro land snail restricted to limestone outcrops in Southeast Asia. Plectostoma was previously classified as a subgenus of Opisthostoma because of the deviation from regular coiling in many species in both taxa. This paper is the first of a two-part revision of the genus Plectostoma, and includes all non-Borneo species. In the present paper, we examined 214 collection samples of 31 species, and obtained 62 references, 290 pictures, and 155 3D-models of 29 Plectostoma species and 51 COI sequences of 19 species. To work with such a variety of taxonomic data, and then to represent it in an integrated, scaleable and accessible manner, we adopted up-to-date cybertaxonomic tools. All the taxonomic information, such as references, classification, species descriptions, specimen images, genetic data, and distribution data, were tagged and linked with cyber tools and web servers (e.g. Lifedesks, Google Earth, and Barcoding of Life Database). We elevated Plectostoma from subgenus to genus level based on morphological, ecological and genetic evidence. We revised the existing 21 Plectostoma species and described 10 new species, namely, P. dindingensis sp. n., P. mengaburensis sp. n., P. whitteni sp. n., P. kayiani sp. n., P. davisoni sp. n., P. relauensis sp. n., P. kubuensis sp. n., P. tohchinyawi sp. n., P. tenggekensis sp. n., and P. ikanensis sp. n. All the synthesised, semantic-tagged, and linked taxonomic information is made freely and publicly available online.

Matched MeSH terms: Computers
Fulltext A functional pipeline framework for landmark identification on 3D surface extracted from volumetric data

Zheng P, Belaton B, Liao IY, Rajion ZA

PLoS One, 2017;12(11):e0187558.
PMID: 29121077 DOI: 10.1371/journal.pone.0187558

Landmarks, also known as feature points, are one of the important geometry primitives that describe the predominant characteristics of a surface. In this study we proposed a self-contained framework to generate landmarks on surfaces extracted from volumetric data. The framework is designed to be a three-fold pipeline structure. The pipeline comprises three phases which are surface construction, crest line extraction and landmark identification. With input as a volumetric data and output as landmarks, the pipeline takes in 3D raw data and produces a 0D geometry feature. In each phase we investigate existing methods, extend and tailor the methods to fit the pipeline design. The pipeline is designed to be functional as it is modularised to have a dedicated function in each phase. We extended the implicit surface polygonizer for surface construction in first phase, developed an alternative way to compute the gradient of maximal curvature for crest line extraction in second phase and finally we combine curvature information and K-means clustering method to identify the landmarks in the third phase. The implementations are firstly carried on a controlled environment, i.e. synthetic data, for proof of concept. Then the method is tested on a small scale data set and subsequently on huge data set. Issues and justifications are addressed accordingly for each phase.

Matched MeSH terms: Computers
Fulltext A high resolution capacitive sensing system for the measurement of water content in crude oil

Zubair M, Tang TB

Sensors (Basel), 2014;14(7):11351-61.
PMID: 24967606 DOI: 10.3390/s140711351

This paper presents the design of a non-intrusive system to measure ultra-low water content in crude oil. The system is based on a capacitance to phase angle conversion method. Water content is measured with a capacitance sensor comprising two semi-cylindrical electrodes mounted on the outer side of a glass tube. The presence of water induces a capacitance change that in turn converts into a phase angle, with respect to a main oscillator. A differential sensing technique is adopted not only to ensure high immunity against temperature variation and background noise, but also to eliminate phase jitter and amplitude variation of the main oscillator that could destabilize the output. The complete capacitive sensing system was implemented in hardware and experiment results using crude oil samples demonstrated that a resolution of ± 50 ppm of water content in crude oil was achieved by the proposed design.

Matched MeSH terms: Computers
Fulltext A novel N-input voting algorithm for X-by-wire fault-tolerant systems

Karimi A, Zarafshan F, Al-Haddad SA, Ramli AR

ScientificWorldJournal, 2014;2014:672832.
PMID: 25386613 DOI: 10.1155/2014/672832

Voting is an important operation in multichannel computation paradigm and realization of ultrareliable and real-time control systems that arbitrates among the results of N redundant variants. These systems include N-modular redundant (NMR) hardware systems and diversely designed software systems based on N-version programming (NVP). Depending on the characteristics of the application and the type of selected voter, the voting algorithms can be implemented for either hardware or software systems. In this paper, a novel voting algorithm is introduced for real-time fault-tolerant control systems, appropriate for applications in which N is large. Then, its behavior has been software implemented in different scenarios of error-injection on the system inputs. The results of analyzed evaluations through plots and statistical computations have demonstrated that this novel algorithm does not have the limitations of some popular voting algorithms such as median and weighted; moreover, it is able to significantly increase the reliability and availability of the system in the best case to 2489.7% and 626.74%, respectively, and in the worst case to 3.84% and 1.55%, respectively.

Matched MeSH terms: Computers
Fulltext A reduced τ-adic Naf (RTNAF) representation for an efficient scalar multiplication on Anomalous Binary Curves (ABC)

Faridah Yunos, Kamel Ariffin Mohd Atan, Muhammad Rezal Kamel Ariffin, Mohamad Rushdan Md Said

Pertanika Journal of Science & Technology, 2014;22(2):489-505.
MyJurnal

Elliptic curve cryptosystems (ECC) provides better security for each bit key utilized compared to the RSA cryptosystem. For this reason, it is projected to have more practical usage than the RSA. In ECC, scalar multiplication (or point multiplication) is the dominant operation, namely, computing nP from a point P on an elliptic curve, where n is an integer defined as the point resulting from adding P + P + ... + P, n times. However, for practical uses, it is very important to improve the efficiency of the scalar multiplication. Solinas (1997) proposes that the τ-adic Non-Adjacent Form (τ-NAF) is one of the most efficient algorithms used to compute scalar multiplications on Anomalous Binary curves. In this paper, we give a new property (i.e., Theorem 1.2) of τ-NAF(n) representation for every length, l. This is useful for evaluating the maximum and minimum norms occurring among all length-l elements of Z(τ). We also propose a new cryptographic method by using randomization of a multiplier n to nr an element of Z(τ). It is based on τ-NAF. We focused on estimating the length of RTNAF(nr) expansion by using a new method.

Matched MeSH terms: Computers
Fulltext A spatial decision support tool for oil palm plantation management

Loh, Kok Fook, Ponusamy, Ragu, Shattri Mansor, Jamil Ismail

Pertanika Journal of Science & Technology, 2009;17(1):-.
MyJurnal

Malaysia is in the process of modernizing its oil palm plantation management, by implementing geo-information technologies which include Remote Sensing (RS), Geographic Information System (GIS), and Spatial Decision Support System (DSS). Agencies with large oil palm plantations such as the Federal Land Development Authority (FELDA), Federal Land Consolidation and Rehabilitation Authority (FELCRA), Guthrie Sdn. Bhd., and Golden Hope Sdn. Bhd. have already incorporated GIS in their plantation management, with limited use of RS and DSS. In 2005, FELCRA, Universiti Putra Malaysia (UPM) and Espatial Resources Sdn. Bhd. (ESR) collaborated in a research project to explore the potentials of geo-informatics for oil palm plantation management. The research was conducted in FELCRA located in Seberang Perak Oil Palm Scheme. In that research, a tool integrating RS, GIS and Analytical Hierarchy Process (AHP) was developed to support decision making for replanting of the existing old palms. RS was used to extract productive stand per hectare; AHP was used to compute the criteria weights for the development of a suitable model; and GIS was used for spatial modelling so as to generate the decision support layer for replanting. This paper highlights the approach adopted in developing the tool with special emphasis on the AHP computation.

Matched MeSH terms: Computers
Fulltext A study of work related complaints of arm, neck and shoulder (CANS) among office workers in Selangor and Kuala Lumpur

Erna Faryza, Mohd Suleiman Murad, Syamsul Anwar

Malaysian Journal of Public Health Medicine, 2015;15(2):8-16.
MyJurnal

The computer is well known as one of the important tools in the office that gives a lot of benefits but silently leads to musculoskeletal pain. There are many different kinds of musculoskeletal complaints pain but the most common seen among computer users in developed countries is the complaint of arm, neck and shoulder (CANS). Despite this, definite factors that can be associated with the prevalence of CANS have not been established. This study was conducted to identify the prevalence and factors associated with work-related complaints of arm, neck and shoulder (CANS) among office workers in Selangor and Kuala Lumpur. A survey study design was conducted where 110 (n=110) office workers were recruited from around the Selangor and Kuala Lumpur area for 5 months periods. Participants were required to answer the Maastricht Upper Extremity Questionnaire (MUEQ) and the Level of Ergonomic Knowledge Questionnaire. The study showed the highest percentage of CANS reported was at neck region (53.6% of participants), followed by shoulders with 53.0%. The majority of participants have low level of computer ergonomic awareness where only 19.09% (n=21) from government sector and 10% (n=11) office workers from private sector reported knowledge of ergonomics. Majority of the participants did not have the know-how in implementing correct computer ergonomics. However there was a weak association (r=

Matched MeSH terms: Computers
A study on the S2 -EWMA chart for monitoring the process variance based on the MRL Performance

Teh Sin Yin, Ong Ker Hsin, Soh Keng Lin, Khoo Michael Boon Chong, Teoh Wei Li

Sains Malaysiana, 2015;44:1067-1075.

The existing optimal design of the fixed sampling interval S2-EWMA control chart to monitor the sample variance of a process is based on the average run length (ARL) criterion. Since the shape of the run length distribution changes with the magnitude of the shift in the variance, the median run length (MRL) gives a more meaningful explanation about the in-control and out-of-control performances of a control chart. This paper proposes the optimal design of the S2-EWMA chart, based on the MRL. The Markov chain technique is employed to compute the MRLs. The performances of the S2-EWMA chart, double sampling (DS) S2 chart and S chart are evaluated and compared. The MRL results indicated that the S2-EWMA chart gives better performance for detecting small and moderate variance shifts, while maintaining almost the same sensitivity as the DS S2 and S charts toward large variance shifts, especially when the sample size increases.

Matched MeSH terms: Computers
Fulltext A systematic review of automated pre-processing, feature extraction and classification of cardiotocography

Al-Yousif S, Jaenul A, Al-Dayyeni W, Alamoodi A, Jabori I, Md Tahir N, et al.

PeerJ Comput Sci, 2021;7:e452.
PMID: 33987454 DOI: 10.7717/peerj-cs.452

Context: The interpretations of cardiotocography (CTG) tracings are indeed vital to monitor fetal well-being both during pregnancy and childbirth. Currently, many studies are focusing on feature extraction and CTG classification using computer vision approach in determining the most accurate diagnosis as well as monitoring the fetal well-being during pregnancy. Additionally, a fetal monitoring system would be able to perform detection and precise quantification of fetal heart rate patterns.
Objective: This study aimed to perform a systematic review to describe the achievements made by the researchers, summarizing findings that have been found by previous researchers in feature extraction and CTG classification, to determine criteria and evaluation methods to the taxonomies of the proposed literature in the CTG field and to distinguish aspects from relevant research in the field of CTG.
Methods: Article search was done systematically using three databases: IEEE Xplore digital library, Science Direct, and Web of Science over a period of 5 years. The literature in the medical sciences and engineering was included in the search selection to provide a broader understanding for researchers.
Results: After screening 372 articles, and based on our protocol of exclusion and inclusion criteria, for the final set of articles, 50 articles were obtained. The research literature taxonomy was divided into four stages. The first stage discussed the proposed method which presented steps and algorithms in the pre-processing stage, feature extraction and classification as well as their use in CTG (20/50 papers). The second stage included the development of a system specifically on automatic feature extraction and CTG classification (7/50 papers). The third stage consisted of reviews and survey articles on automatic feature extraction and CTG classification (3/50 papers). The last stage discussed evaluation and comparative studies to determine the best method for extracting and classifying features with comparisons based on a set of criteria (20/50 articles).
Discussion: This study focused more on literature compared to techniques or methods. Also, this study conducts research and identification of various types of datasets used in surveys from publicly available, private, and commercial datasets. To analyze the results, researchers evaluated independent datasets using different techniques.
Conclusions: This systematic review contributes to understand and have insight into the relevant research in the field of CTG by surveying and classifying pertinent research efforts. This review will help to address the current research opportunities, problems and challenges, motivations, recommendations related to feature extraction and CTG classification, as well as the measurement of various performance and various data sets used by other researchers.

Matched MeSH terms: Computers
Fulltext ARTYCUL: A Privacy-Preserving ML-Driven Framework to Determine the Popularity of a Cultural Exhibit on Display

Tanwar G, Chauhan R, Yafi E

Sensors (Basel), 2021 Feb 22;21(4).
PMID: 33671822 DOI: 10.3390/s21041527

We present ARTYCUL (ARTifact popularitY for CULtural heritage), a machine learning(ML)-based framework that graphically represents the footfall around an artifact on display at a museum or a heritage site. The driving factor of this framework was the fact that the presence of security cameras has become universal, including at sites of cultural heritage. ARTYCUL used the video streams of closed-circuit televisions (CCTV) cameras installed in such premises to detect human figures, and their coordinates with respect to the camera frames were used to visualize the density of visitors around the specific display items. Such a framework that can display the popularity of artifacts would aid the curators towards a more optimal organization. Moreover, it could also help to gauge if a certain display item were neglected due to incorrect placement. While items of similar interest can be placed in vicinity of each other, an online recommendation system may also use the reputation of an artifact to catch the eye of the visitors. Artificial intelligence-based solutions are well suited for analysis of internet of things (IoT) traffic due to the inherent veracity and volatile nature of the transmissions. The work done for the development of ARTYCUL provided a deeper insight into the avenues for applications of IoT technology to the cultural heritage domain, and suitability of ML to process real-time data at a fast pace. While we also observed common issues that hinder the utilization of IoT in the cultural domain, the proposed framework was designed keeping in mind the same obstacles and a preference for backward compatibility.

Matched MeSH terms: Computers
Fulltext Adapting non-standard weighted average approach for solving the Lotka-Volterra model

Mohammad Khatim Hasan, Shahrizan Mazlan

Pertanika Journal of Science & Technology, 2017;25(106):97-106.
MyJurnal

Simulating Lotka-Volterra model using a numerical method requires the researcher to apply tiny mesh sizes to come up with an accurate solution. This approach will increase the complexity and burden of computer memory and consume long computational time. To overcome these issues, a new solver is used that could simulate Lotka-Volterra model using bigger mesh size. In this paper, prey and predator behaviour is simulated via Lotka-Volterra model. We approximate the nonlinear terms in the model via weighted average approach and differential equation via nonstandard denominators. We provide three new schemes for one step method and simulate four sets of parameters to examine the performance of these new schemes. Results show that these new schemes simulate better for large mesh sizes.

Matched MeSH terms: Computers
Adoption of clinical decision support systems in a developing country: Antecedents and outcomes of physician's threat to perceived professional autonomy

Esmaeilzadeh P, Sambasivan M, Kumar N, Nezakati H

Int J Med Inform, 2015 Aug;84(8):548-60.
PMID: 25920928 DOI: 10.1016/j.ijmedinf.2015.03.007

The basic objective of this research is to study the antecedents and outcomes of professional autonomy which is a central construct that affects physicians' intention to adopt clinical decision support systems (CDSS). The antecedents are physicians' attitude toward knowledge sharing and interactivity perception (about CDSS) and the outcomes are performance expectancy and intention to adopt CDSS. Besides, we include (1) the antecedents of attitude toward knowledge sharing-subjective norms, social factors and OCB (helping behavior) and (2) roles of physicians' involvement in decision making, computer self-efficacy and effort expectancy in our framework.

Matched MeSH terms: Attitude to Computers*
Fulltext Advancements in Monitoring Water Quality Based on Various Sensing Methods: A Systematic Review

Zainurin SN, Wan Ismail WZ, Mahamud SNI, Ismail I, Jamaludin J, Ariffin KNZ, et al.

Int J Environ Res Public Health, 2022 Oct 28;19(21).
PMID: 36360992 DOI: 10.3390/ijerph192114080

Nowadays, water pollution has become a global issue affecting most countries in the world. Water quality should be monitored to alert authorities on water pollution, so that action can be taken quickly. The objective of the review is to study various conventional and modern methods of monitoring water quality to identify the strengths and weaknesses of the methods. The methods include the Internet of Things (IoT), virtual sensing, cyber-physical system (CPS), and optical techniques. In this review, water quality monitoring systems and process control in several countries, such as New Zealand, China, Serbia, Bangladesh, Malaysia, and India, are discussed. Conventional and modern methods are compared in terms of parameters, complexity, and reliability. Recent methods of water quality monitoring techniques are also reviewed to study any loopholes in modern methods. We found that CPS is suitable for monitoring water quality due to a good combination of physical and computational algorithms. Its embedded sensors, processors, and actuators can be designed to detect and interact with environments. We believe that conventional methods are costly and complex, whereas modern methods are also expensive but simpler with real-time detection. Traditional approaches are more time-consuming and expensive due to the high maintenance of laboratory facilities, involve chemical materials, and are inefficient for on-site monitoring applications. Apart from that, previous monitoring methods have issues in achieving a reliable measurement of water quality parameters in real time. There are still limitations in instruments for detecting pollutants and producing valuable information on water quality. Thus, the review is important in order to compare previous methods and to improve current water quality assessments in terms of reliability and cost-effectiveness.

Matched MeSH terms: Computers

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