Farhan Ullah

Semantic Interoperability in Heterogeneous IoT Infrastructure for Healthcare

Interoperability remains a significant burden to the developers of Internet of Things’ Systems. This is due to the fact that the IoT devices are highly heterogeneous in terms of underlying communication protocols, data formats, and technologies. Secondly due to lack of worldwide acceptable standards, interoperability tools remain limited. In this paper, we proposed an IoT based Semantic Interoperability Model (IoT-SIM) to provide Semantic Interoperability among heterogeneous IoT devices in healthcare domain. Physicians communicate their patients with heterogeneous IoT devices to monitor their current health status. Information between physician and patient is semantically annotated and communicated in a meaningful way. A lightweight model for semantic annotation of data using heterogeneous devices in IoT is proposed to provide annotations for data. Resource Description Framework (RDF) is a semantic web framework that is used to relate things using triples to make it semantically meaningful. RDF annotated patients’ data has made it semantically interoperable. SPARQL query is used to extract records from RDF graph. For simulation of system, we used Tableau, Gruff-6.2.0, and Mysql tools.

Multiagent Semantical Annotation Enhancement Model for IoT-Based Energy-Aware Data

The Internet of Things (IoT) is involved in dealing with physical items, gadgets, vehicles, structures, and different things that are inserted into hardware, programming, sensors, and system availability, which empowers these items to gather and trade information. Improving extraction of sensor-based data for energy awareness and then annotating it and converting it into semantically enabled form for analyzing results with the use of improved tools and applications are the focus of this research. However, as the amount of real time data gets huge, it becomes difficult to track results when needed at once. Reconciliation of heterogeneous information sources into an interlinked data is a standout among the most pertinent difficulties for some learning based systems these days. This paper forms suitable elements by a methodology for adjustment of heterogeneous sensor-based Web assets, where different tools and applications like weather detection for self-observing and self-diagnostics use dispersed human specialists and learning. The proposed general model uses a capability of the Semantic Web innovation and concentrates on the part of a semantic adjustment of existing broadly utilized models of information representation to Resource Description Framework (RDF) based semantically rich arrangement. This work is valuable for sorting out and inquiry of the detecting information in the Internet of Things.

LSA Based Smart Assessment Methodology for SDN Infrastructure in IoT Environment

The Software Defined Network (SDN) is merged in the Internet of Things (IoT) to interconnect large and complex networks. It is used in the education system to interconnect students and teacher by heterogenous IoT devices. In this paper, the SDN-based IoT model for students’ Interaction is proposed which interconnects students to a teacher in a smart city environment. The students and teachers are free to move to anywhere, anytime and with any hardware. An architecture model for students’ teacher’s interaction in IoT is proposed which shows the details procedure about the interaction of teacher with students for electronic assessment. The SDN solves the scalability and interoperability issues between their heterogenous IoT devices. A Methodology for Students’ Answer Assessment using Latent Semantic Analysis (LSA) is proposed which calculates the semantic similarity between teacher’s question and students’ answers. The LSA is used to calculate semantic similarity between text documents. It is used to mark the students’ answers automatically by semantics. The Students’ can see results through their IoT devices just after finishing the examination with more accurate marks We have collected fifty (50) undergraduate students’ data from Learning Management System (LMS) of Virtual University (VU) of Pakistan. The experiment is implemented on eighteen (18) students’ answers in R Studio with R version 3.4.2. Teachers are provided with four (4) bins of the mark while the proposed method assigns accurate marks. The experimental results show that the proposed methodology gave accurate results as compared to teacher’s marks.

Plagiarism detection in students’ programming assignments based on semantics: multimedia e-learning based smart assessment methodology

The multimedia-based e-Learning methodology provides virtual classrooms to students. The teacher uploads learning materials, programming assignments and quizzes on university’ Learning Management System (LMS). The students learn lessons from uploaded videos and then solve the given programming tasks and quizzes. The source code plagiarism is a serious threat to academia. However, identifying similar source code fragments between different programming languages is a challenging task. To solve the problem , this paper proposed a new plagiarism detection technique between C++ and Java source codes based on semantics in multimedia-based e-Learning and smart assessment methodology. First, it transforms source codes into tokens to calculate semantic similarity in token by token comparison. After that, it finds semantic similarity in scalar value for the complete source codes written in C++ and Java. To analyse the experiment, we have taken the dataset consists of four (4) case studies of Factorial, Bubble Sort, Binary Search and Stack data structure in both C++ and Java. The entire experiment is done in R Studio with R version 3.4.2. The experimental results show better semantic similarity results for plagiarism detection based on comparison.

Formal modeling of smart logistics monitoring

In this paper, we present orders, customers, products, manufacturer, warehouse, transportation and payments components of our proposed smart logistics monitoring system model. This paper presents model which provide smart logistics service, identify customer demands, products and inventory management to develop smart logistics system. Four modules system management, order, customers, and manufacturer are described only here. It involves the wireless sensors, RFID, RTLS and actors to communicate with different components of the system. The proposed components require fewer resources in terms of sensors, RFID, RTLS, and actors. Further, sensors identify objects through RFID and it is readable through sensors from its barcode and barcode consists of objects details in terms of order registration, type, price, and color. The components of our proposed model are implemented by developing formal specification using VDM-SL, which is a formal specification language used for analysis of complex systems. The developed specification is validated, verified and analyzed using VDM-SL Toolbox.

Formal modeling of smart home monitoring system

In this paper, we describe smart sensors, actors, user, alarm system, smart appliances of our proposed smart home model. We also describe the main problems of the smart home which are safety, security and energy saving. In our smart home model wireless sensor, actors, smart appliances, and user communicate with each other and with the central system. Sensors collect data about abnormal home situations or events and send this data to the central system. The system further communicates with the user and events are handled by the central system, user and smart actors depending upon the nature of the event. Actors perform necessary functions on the basis of information provided by the sensor. Sensors are installed at different locations in the home. The components of our proposed smart home model are implemented by developing a formal specification of components using VDM-SL. VDM-SL is a formal specification language used for analysis of complex systems. The developed specification is validated, verified and analysed using.

Formal Modeling and Verification of Smart Traffic Environment with Design Aided by UML

Issue challan in response to rules violation, LED (Light Emitting Diode) and Bridge components of this proposed Smart Traffic Monitoring and Guidance System are presented in this paper to monitor violation of rules, update users about traffic congestion through LED and to provide central hub to communicate with sensors to update server about the traffic situation. It involves the Wireless Sensors and actors to communicate with the system. The proposed components require fewer resources in terms of sensors and actors. Further sensors identify violation of rules through issue challan. Secondly, LED component provides information to users about the traffic situations. Thirdly, Bridge component is used to provide central hub to communicate with different components in the proposed model and to update the server. The proposed components of this model are implemented by developing formal specification using VDM-SL. VDM-SL is a formal specification language used for analysis of complex systems. The developed specification is validated, verified and analyzed using VDM-SL Toolbox.