A Multi-Layer Sensing As A Service Model Based On Internet Of Things For Smart-Healthcare Applications

Smart healthcare services have been known for requiring huge concentricity of information resources and establishments. However, unprecedented attraction of offering new technologies has now become an overwhelming resource management issue for healthcare service providers. The tremendous demands toward effective smart healthcare administration seems to have prompted to develop various ICT technologies in finding advantageous solutions to positively solve the increasing problems. The Internet of Things (IoT) even offers considerable interest to deliver an efficient resource management in Smart healthcare services. Such tremendous smart IoT health devices that linked to the internet could very well provide various types of service solutions and generate a big amount of data and information. However, most applications that may have interaction with smart IoT health devices just like sensors come with particular requirements to allow real time processing for different data types. In this paper, we introduce a multi-layer Sensing as a Service model as well as, clarifying how it end up being addressed by the concept of IoT. Our target is definitely to investigate the IoT technologies towards the delivery of Sensing as a Service with regard to the technical perspective and recognize the key available problems. We also illustrate the proposed multi-layer sensing as a service modelbyemployingthe scenario of smart healthcare application. Finally, discussion has been delivered for providing the major advantages and benefits of our proposed model

Sentimental classification analysis of polarity multi-view textual data using data mining techniques

The data and information available in most community environments is complex in nature. Sentimental data resources may possibly consist of textual data collected from multiple information sources with different representations and usually handled by different analytical models. These types of data resource characteristics can form multi-view polarity textual data. However, knowledge creation from this type of sentimental textual data requires considerable analytical efforts and capabilities. In particular, data mining practices can provide exceptional results in handling textual data formats. Besides, in the case of the textual data exists as multi-view or unstructured data formats, the hybrid and integrated analysis efforts of text data mining algorithms are vital to get helpful results. The objective of this research is to enhance the knowledge discovery from sentimental multi-view textual data which can be considered as unstructured data format to classify the polarity information documents in the form of two different categories or types of useful information. A proposed framework with integrated data mining algorithms has been discussed in this paper, which is achieved through the application of X-means algorithm for clustering and HotSpot algorithm of association rules. The analysis results have shown improved accuracies of classifying the sentimental multi-view textual data into two categories through the application of the proposed framework on online polarity user-reviews dataset upon a given topics

Analysis of Mobile Service Providers Performance Using Naive Bayes Data Mining Technique

Recently, the mobile service providers have been growing rapidly in Malaysia. In this paper, we propose analytical method to find best telecommunication provider by visualizing their performance among telecommunication service providers in Malaysia, i.e. TM Berhad, Celcom, Maxis, U-Mobile, etc. This paperuses data mining technique to evaluate the performanceof telecommunication service providers using their customers feedback from Twitter Inc. It demonstrates on how the system could process and then interpret the big data into a simple graph or visualization format. In addition, build a computerized tool and recommend data analytic model based on the collected result. From prepping the data for pre-processing until conducting analysis, this project is focusing on the process of data science itself where Cross Industry Standard Process for Data Mining (CRISP-DM) methodology will be used as a reference. The analysis was developed by using R language and R Studio packages. From the result, it shows that Telco 4 is the best as it received highest positive scores from the tweet data. In contrast, Telco 3 should improve their performance as having less positive feedback from their customers via tweet data. This project bring insights of how the telecommunication industries can analyze tweet data from their customers. Malaysia telecommunication industry will get the benefit by improving their customer satisfaction and business growth. Besides, it will give the awareness to the telecommunication user of updated review from other users

Clustering Methods For Cluster-Based Routing Protocols In Wireless Sensor Networks: Comparative Study

Wireless Sensor Networks are used in large area of applications since they can be suitable for various environments. It can function independently in the condition of harsh or risk places where a human's apparition is impossible or very hard. Nevertheless, the sensor's life-time is only related to their batteries, which are impossible for replacing or recharging. So, the energy-efficient routing protocols are very necessary and considers vital task for sensors networks. Various approaches of clustering algorithms are used to optimize the energy of routing protocols. Also, the clustering approaches support the scalability of Wireless Sensor Networks. In this paper, numerous energy efficient routing algorithms for hierarchical routing protocol in Wireless Sensor Networks have been discussed based on the clustering approaches. These approaches of clustering algorithms whether Distributed, Centralized, or Hybrid are reviewed very well, since the most of clustering algorithms have been developed by many researches based on these approaches. Our objective is exploring the literature to present a brief discussion of these algorithms, as well as examine and compare some of distributed, centralized and hybrid clustering algorithm based on several attributes. This work aims to give a clear vision for the developers and researchers about cluster-based hierarchical routing protocols, and how can classified the clustering approaches according to literatures

A Review On IoT-Based Healthcare Monitoring Systems For Patient In Remote Environments

The Internet of Things (IoT) is a powerful technology that can enable users’ smart devices and sensors to link each other and access the internet for daily usage. It is a platform that can be used by end users to access many smart application fields, such as smart city, smart home, and smart healthcare. In recent years, the healthcare monitoring systems are becoming the major development field that use the IoT as advanced technology enabler. This review is discussing more about the design, functions, and the main uses of the IoT-based healthcare monitoring applications and systems for remote patient environments. Therefore, a deep review has been made to identify the usage, efficiency, and acceptability for the current applications and systems to become more efficient to patients. Different healthcare monitoring systems have employed the IoT to integrate the different wireless interfaces with the cloud-based healthcare services. These services are including the sensing, gathering, processing, storing, and learning more among the patients’ data. The various IoT healthcare applications will help to develop useful and effective solutions by using these systems in practice. From this review it can be proof that the IoT-based healthcare monitoring applications are growing faster to build more healthcare solutions that useful for different healthcare conditions and environment

Clustering Approach In Wireless Sensor Networks Based On K-Means: Limitations And Recommendations

Clustering approach in wireless sensor network is very important, the structure of cluster and how to improve it is a first challenge that faced the developers, because of it represent as a base for design the cluster-based routing protocol. One of most popular cluster algorithms that utilizing into organize sensor nodes is K-means algorithm. This algorithm has beneficial in construct the clusters for various real-world applications of WSN.K-means algorithm suffering from many drawbacks that hampering his work.The lack of adequate studies that investigates in the limitations of this algorithm and seek to propose the solutions motivated us to do this study. In this paper the limitations of K-means and some suggestions are proposed. These suggestions can improve the performance of K-means, which will be reflected on saving the energy forsensor nodes and consequently maximize the lifetime of the wireless sensor networks

Internet Of Things Architecture:Current Challenges And Future Direction Of Research

The Internet of Things (IoT) is a new paradigm that can enable collecting and exchanging data that have never been attainable before.It able to communicate and report user’s information in a more secure way.The reports of Cisco analysts estimate that the IoT will have more than 50 billion of smart sensors and other smart devices or gadgets,all connecting and communicating real time data on the internet by 2020.This will provide deeper insights with data analytics using the IoT paradigm to establish new business,enhance productivity and efficiency,and develop innovative revenue streams.Furthermore,the IoT architecture may combine features and technologies suggested by various methodologies.Since,this architecture is designed where the digital and real worlds are integrating and interacting constantly,various technologies are merged together to form IoT,such as; sensing technologies,pervasive computing,ubiquitous computing,internet protocols,smart objects,embedded parts,etc.When a regular device utilizes intelligent agents,it becomes a smart object.In this way,it is not only used to gather the environment information or interact with the physical world,yet more than that,it must be interconnected with various network devices to exchange and communicate data over the internet. Therefore,the significant measure of available data which is produced by the immense number of interconnected devices will offer opportunities to generate information that will deliver significant benefits to the economy, environment,individuals,and society.In this paper,we present past,current,and future direction of IoT.This paper provides overview and clear examination of the IoT architecture paradigm with the description of its fundamental requirements along with the implementation challenges and future directions.Thus,it will open issues that will face the IoT by new world generation

A Review on Security Challenges and Features in Wireless Sensor Networks: IoT Perspective

The Internet of Things is becoming a very promising paradigm with the extensive market adoption of the development of associated technologies, such as; cloud computing, near-field communications, wireless mobile networks, etc. This will expose the future direction of communication around the world. Wireless Sensor Networks together with the existing communication technologies are enabling the continuous integration of controlling and processing the functionality of the Internet of Things applications. Since Wireless Sensor Networks are typically deployed for gathering sensitive information from unattended or hostile environments, they are exposed for security attacks, which are strongly affecting the user privacy and the network performance. There are various security mechanisms and solutions for Wireless Sensor Networks that have been proposed in the previous works. Therefore, it is mandatory to give attention for its applicability and feasibility features in terms of related security challenges based on the Internet of Things perspectives. The purpose of this paper is to explore and show the influence of Wireless Sensor Networks security challenges within the perspective of the Internet of Things and its applications. Consequently, an exploration of the major and minor security requirements in the Wireless Sensor Networks has been made in this paper, accompanied by a classification of the available attacks and threats against these requirements. Finally, a discussion on the Internet of Things security issues and challenges in Wireless Sensor Networks is provided

Multi-Objectives Ant Colony System For Solving Multi-Objectives Capacitated Vehicle Routing Problem

As a combinatorial optimization problem, the capacitated vehicle routing problem (CVRP) is a vital one in the domains of distribution, transportation and logistics. Despite the fact that many researchers have solved the problem using a single objective, only little attention has been given to multi-objective optimization. As compared to multi-objectives, the comparison of solutions is easier with single-objective optimization fitness function. In this paper, the following objectives were achieved: (i) in view of the domain of the multiobjective CVRP, the total distance traveled by the vehicles and the total number of vehicles used are reduced, and (ii) in the view of the technique, a multi-objective Ant Colony System is proposed to solve the multiobjective of CVRP based on the experience of sub-paths. The proposed algorithm was evaluated using some standard benchmark problems of CVRP. The results show that the algorithm which has been proposed in this study is highly competitive and quite effective for multi-objective optimization of CVR

Epidemiology of Chlamydia trachomatis in the Middle East and north Africa: a systematic review, meta-analysis, and meta-regression.

BACKGROUND: The epidemiology of Chlamydia trachomatis in the Middle East and north Africa is poorly understood. We aimed to provide a comprehensive epidemiological assessment of C trachomatis infection in the Middle East and north Africa. METHODS: We did a systematic review of C trachomatis infection as well as a meta-analysis and meta-regression of C trachomatis prevalence. We searched PubMed and Embase, as well as regional and national databases up to March 13, 2019, using broad search terms with no language or year restrictions. Any document or report including biological measures for C trachomatis prevalence or incidence was eligible for inclusion. We extracted all measures of current (genital or rectal), recent, and ever infection with C trachomatis. We estimated pooled average prevalence in different populations using random-effects meta-analysis. Factors associated with prevalence and sources of between-study heterogeneity were determined using meta-regression. FINDINGS: We identified a total of 1531 citations, of which 255 reports contributed to 552 C trachomatis prevalence measures from 20 countries. No incidence measures were identified. Pooled prevalence of current genital infection was 3·0% (95% CI 2·3-3·8) in general populations, 2·8% (1·0-5·2) in intermediate-risk populations, 13·2% (7·2-20·7) in female sex workers, 11·3% (9·0-13·7) in infertility clinic attendees, 12·4% (7·9-17·7) in women with miscarriage, 12·4% (9·4-15·7) in symptomatic women, and 17·4% (12·5-22·8) in symptomatic men. Pooled prevalence of current rectal infection was 7·7% (4·2-12·0) in men who have sex with men. Substantial between-study heterogeneity was found. Multivariable meta-regression explained 29·0% of variation. Population type was most strongly associated with prevalence. Additional associations were found with assay type, sample size, country, and sex, but not with sampling methodology or response rate (about 90% of studies used convenience sampling and >75% had unclear response rate). There was no evidence for temporal variation in prevalence between 1982 and 2018. INTERPRETATION: C trachomatis prevalence in the Middle East and north Africa is similar to other regions, but higher than expected given its sexually conservative norms. High prevalence in infertility clinic attendees and in women with miscarriage suggests a potential role for C trachomatis in poor reproductive health outcomes in this region. FUNDING: National Priorities Research Program from the Qatar National Research Fund (a member of Qatar Foundation)