Mobile sensing and social computing

With the rapid development of social networks and social environments, mobile sensing has increasingly emerged as one of the most important technologies to develop social computing solutions. Social computing is a general term for an area of computer science that is concerned with the intersection of social behavior and computational systems, providing a programmable combination of contributions from both humans and computers. A key factor for social computing is how social information is collected from the ubiquitous environments and can be widely used to provide social services in mobile environments. Mobile sensing is increasingly becoming part of everyday life, as smartphones are becoming the central personal computational device in people’s lives. Mobile sensing presents several challenges related to wireless sensor networks, machine learning, human–computer interaction, and mobile systems. Sensor-equipped mobile phones can be combined with wireless sensor networks installed in the environment to develop social machines in many sectors of our economy, including business, healthcare, social networks, environmental monitoring, and transportation. Some research efforts on social computing and mobile sensing have been in progress, including mobile sensing algorithms, applications and systems, and methods and techniques to develop virtual societies. This IJDSN Special Issue is an opportunity to bring multi-disciplinary experts, academics, and practitioners together to exchange their experience in the development and deployment of mobile sensing and social computing systems. This Special Issue brings together researchers and developers from industry and academy to report on the latest scientific and technical advances on the application of mobile sensing and social computing and to showcase the latest systems using these technologies. Filipe et al. compile and compare technologies and protocols published in the most recent researches, seeking Wireless Body Area Network (WBAN) issues for medical monitoring purposes to select the most useful solutions for this area of networking. The most important features under consideration in our analysis include wireless communication protocols, frequency bands, data bandwidth, transmission distance, encryption, authentication methods, power consumption, and mobility. WBAN supporting healthcare applications are in early development stage, but offer valuable contributions at monitoring, diagnostic, or therapeutic levels. They cover real-time medical information gathering obtained from different sensors with secure data communication and low power consumption. Filipe et al. demonstrate that some characteristics of surveyed protocols are very useful to medical appliances and patients in a WBAN domain. Marcelino et al. present a solution to overcome barriers between elderlies and their information and communication technology (ICT) usage in order to potentiate all the benefits provided from mobile sensing and social computing. They present a survey on guidelines, standards, and advices regarding usability and accessibility issues when developing solutions for elderly people made having in mind that senior population have singular requirements due to age-related changes and also frequently technological illiteracy. The authors have identified and applied the most important guidelines to their own solution. A prototype was made using responsive design in order to be adaptable to any type of devices. Zong and Wen propose a new approach to calculate the smartphone orientation by detecting the vehicle starting action and then establish the coordinate system relationship between vehicle and smartphone. Furthermore, they trained the classified model offline to match the acceleration characteristics with traveling speed. In the model training process we compared different classification algorithms. Due to enclosed areas and intensive energy consumption, GPS or WiFi sometime are invalid. In this paper, Zong and Wen propose a new approach to estimate the traveling speed after analyzing the acceleration characteristics in time domain and frequency domain. Shuyun et al. propose a method used to calculate the link importance degree index, and the index is used to evaluate the link’s information. Besides, a multiobjective optimization model is proposed, its aim is to minimize the total cruise time under detecting as many important links as possible and minimize the information value undetected by unmanned aerial vehicles (UAVs), and the fuzzy operator is introduced to the constraint conditions. Finally, a case study is used to