Security and the smart city: A systematic review

Wireless Body Area Network is an emerging technology that is used primarily in the area of healthcare applications. It is a low-cost network having the capability of transportability and adaptability. It can be used in location independent and long-term remote monitoring of people without disturbing their daily activities. In a typical WBAN system, sensing devices are either implanted or etched into the human body that continuously monitors his physiological parameters or vital signs. In such a network, trusts among the stakeholders (healthcare providers, users, and medical staff, etc.) are found of high importance and regarded as the critical success factor for the reliability of information exchange among them. In remote patient monitoring, the implementation of trust and privacy preservation is crucial, as vital parameters are being communicated to remote locations. Nonetheless, its widespread use, WBAN, has severe trust and privacy risks, limiting its adaptation in healthcare applications. To address trust and privacy-related issues, reliable communication solutions are widely used in WBANs. Given the motivation, in this paper, we have proposed a trust-based communication scheme to ensure the reliability and privacy of WBAN. To ensure reliability, a cooperative communication approach is used, while for privacy preservation, a cryptography mechanism is used. The performance of the proposed scheme is evaluated using MATLAB simulator. The output results demonstrated that the proposed scheme increases service delivery ratio, reliability, and trust with reduced average delay. Furthermore, a fuzzy-logic method used for ranking benchmark schemes, that has been concluded that the proposed scheme has on top using comparative performance ranking.

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A Trust-Based Energy-Efficient and Reliable Communication Scheme (Trust-Based ERCS) for Remote Patient Monitoring in Wireless Body Area Networks

Traffic management system is a cornerstone of a Smart city. In the current problems of the world, urban mobility is one of the major problems, especially in metropolitan cities. Previous traffic management systems are not capable enough to tackle this growth of traffic on the road networks. The purpose of this paper is to propose a smart traffic management system using the Internet of Things and a decentralized approach to optimize traffic on the roads and intelligent algorithms to manage all traffic situations more accurately. This proposed system is overcoming the flaws of previous traffic management systems. The system takes traffic density as input from cameras which is abstracted from Digital Image Processing technique and sensors data, resultantly giving output as signals management. An algorithm is used to predicts the traffic density for future to minimize the traffic congestion. Besides this, RFIDs are also used to prioritize the emergency vehicles like ambulance, fire brigade etc. by implementing RFID tags in such vehicles. In the case of emergency situations, such as fire explosion or burning of something, fire and smoke sensors are also deployed on the road to detect such situations. Moreover, a mobile application is connected to a centralized server which intimates to nearby rescue department about fire explosion with the location to take further action. In addition, the native user can ask about future traffic condition at a particular node. The proposed system is validated by constructing a prototype and deploying it in a city of Pakistan. A web application is also there to provide useful information in graphical formats to the higher authorities of the smart city which is fruitful in future road planning.

Smart traffic management system using Internet of Things

Computer vision has evolved in the last decade as a key technology for numerous applications replacing human supervision. Timely detection of traffic violations and abnormal behavior of pedestrians at public places through computer vision and visual surveillance can be highly effective for maintaining traffic order in cities. However, despite a handful of computer vision–based techniques proposed in recent times to understand the traffic violations or other types of on-road anomalies, no methodological survey is available that provides a detailed insight into the classification techniques, learning methods, datasets, and application contexts. Thus, this study aims to investigate the recent visual surveillance–related research on anomaly detection in public places, particularly on road. The study analyzes various vision-guided anomaly detection techniques using a generic framework such that the key technical components can be easily understood. Our survey includes definitions of related terminologies and concepts, judicious classifications of the vision-guided anomaly detection approaches, detailed analysis of anomaly detection methods including deep learning–based methods, descriptions of the relevant datasets with environmental conditions, and types of anomalies. The study also reveals vital gaps in the available datasets and anomaly detection capability in various contexts, and thus gives future directions to the computer vision–guided anomaly detection research. As anomaly detection is an important step in automatic road traffic surveillance, this survey can be a useful resource for interested researchers working on solving various issues of Intelligent Transportation Systems (ITS).

Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey

Image fusion plays a significant role in various computer vision applications. However, designing an efficient image fusion technique is still a challenging task. In this paper, a novel deep belief networks based image fusion framework is proposed to improve the performance of the image fusion process further. We have initially, evaluated the fusion dataset by applying various feature extraction techniques. Thereafter, features selection techniques are applied to select potential features. Finally, the image fusion machine learning model is built by using a deep belief network model. Extensive experiments reveal that the proposed technique outperforms existing image fusion techniques.

Fusion of medical images using deep belief networks

Micromanipulation has become a significant task in the fields of microelectromechanical systems, cell biology and cell mechanics in past few decades To study cell mechanics and cell biology, samples are required In general, these samples are taken with the help of a microgripper, also known as micro-tweezer and micromanipulator In this paper, a biocompatible microgripper design is presented for single cell manipulation SU-8 material is selected due to biocompatibility and thermal properties for microgripper design Electrothermal actuators are used to provide input displacement and force to compliant mechanism Compliant mechanism include Scott Russell mechanism, Multi-stage Compound Radial Flexure and leverage mechanism, which provide amplification in output displacement at low power Response of microgripper is close to linear for accurate and intelligent manipulation task Jaws are designed to grip cells and objects of various shapes and sizes Results are produced using finite element analysis software, to check the usability of design for biomedical applications 30 μm displacement is achieved at low voltage of 50 mV, keeping temperature of gripping jaws at room temperature

Design of an Electrothermally Actuated SU-8 Based Microgripper for Biomedical Applications

The importance of identifying and tackling different risks faced by Pakistani IT companies in the 21st century are much more diverse and varying then those that were faced 50 years ago. In this paper we perform a survey of the different kinds of risks faced by IT companies in Pakistan. The survey helps us to identify the faults of companies that lead them to encountering of these risks. We are facing much loss in our IT sector due to the risks faced by companies in our country and this survey helps us emphasize the importance of risk management for IT companies. The survey findings will certainly help both researchers and practitioners in future to carry out risk management research keeping the particular risks faced in our country in mind.

Identification of risks in Pakistani IT companies: A survey paper

Three Tier Unified Process Model for Requirement Negotiations and Stakeholder Collaborations

Software Projects Outsourcing is used extensively by different organizations as a sourcing strategy today and it becomes a crucial issue in achieving specific objective. This paper studies the impact of management issues on the effectiveness of outsourcing of software projects in industries of Pakistan. Outsourcing is an imperative trend in now a day's business environment and is vital for us to well comprehend what factors influence more on outsourcing. On basis of literature review this paper recognizes main management issues that the client organization needs to possess to efficiently outsource software projects. Quantitative data from different several software fields is utilized to support the findings that what factors are more influencing during outsourcing for different industries. Different factors are identified and highlighted to catch the weaknesses which occur during successful outsourcing of software projects.

Highlighting Management Issues Affecting Outsourcing in Pakistan's Software Industry

Text summarization has become a sophisticated approach for the quick searching, automatic sorting, abstract generating etc., to the large amount of data. The involvement of complete study of passage and extra time is needed to generate the essence of any content. Subsequently, Natural Language Processing is an information extraction approach to automatically extract the artifacts from the textual descriptions. Moreover, NLP is often applied to generate the various element of concerns like essential terms, class models, test cases from the initial Textual descriptions. However, it is usually required to study complete passage to extract relevant information from textual content that makes this process time consuming. This research article proposed a novel and fully automatic NLP methodology to generate crux from content. As a part of research, a tool Efficient Text Summary from Text (ETST) is developed. Research authentication is achieved through the implementation of two state-of-the-art case studies. The experimental outcome proved that our suggested Natural Language Processing methodology is novel and fully automatic and is also useful for the future researchers of this domain.

Muhammad Abbas

Papers

Design of an Electrothermally Actuated SU-8 Based Microgripper for Biomedical Applications

Identification of risks in Pakistani IT companies: A survey paper

Three Tier Unified Process Model for Requirement Negotiations and Stakeholder Collaborations

Highlighting Management Issues Affecting Outsourcing in Pakistan's Software Industry

A Novel NLP Application to Automatically Generate Text Extraction Concepts from Textual Descriptions