The possibility of sensing and predicting the movements of crowds in modern cities is of fundamental importance for improving urban planning, urban mobility, urban safety, and tourism activities. However, it also introduces several challenges at the...
The proliferation of mobile devices such as smartphones and tablets with embedded sensors and communication features has led to the introduction of a novel sensing paradigm called mobile crowd sensing. Despite its opportunities and advantages over tr...
In the process of completing large-scale and fine-grained sensing tasks for the new generation of crowd-sensing systems, the role of analysis, reasoning, and decision making based on artificial intelligence has become indispensable. Mobile crowd sens...
Spectrum sensing is the prerequisite of the realization of cognitive radio. So it is a significant part of cognitive radio. In order to stimulate the SUs to sense the spectrum, we combine the incentive mechanism of crowd-sensing with cooperative spec...
Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system s...
Crowd sensing is a perception mode that recruits mobile device users to complete tasks such as data collection and cloud computing. For the cloud computing platform, crowd sensing can not only enable users to collaborate to complete large-scale aware...
Having an incentive mechanism is crucial for the recruitment of mobile users to participate in a sensing task and to ensure that participants provide high-quality sensing data. In this paper, we investigate a staged incentive and punishment mechanism...
Crowd sensing is a powerful tool to map and predict interests and events. In the future, it could be boosted by an increasing number of connected vehicles sharing information and intentions. This will be made available by on board wireless connected...
Co-operative spectrum sensing emerging as a significant method to improve the utilization of the spectrum needs sufficient sensing users to participate. Existing related papers consider only the limited secondary users in current sensing system and a...
Mobile crowd sensing (MCS) is an application that collects data from a network of conscientious volunteers and implements it for the common or personal benefit. This contribution proposes an implementation that collects the data from hypertensive pat...
The proliferation of numerous portable mobile devices has made mobile crowd-sensing (MCS) systems a promising new trend. Traditional MCS systems typically outsource sensing tasks to the data aggregator (e.g., cloud server). They collect and analyze t...
The Internet of Things (IoT) concept is aiming at being an integral part of the next generation networking services by introducing pervasiveness and ubiquitous interconnectivity of uniquely-identifiable objects. The massive availability of personaliz...
Mobile crowd sensing (MCS) is a new sensing paradigm that leverages participatory sensing data from mobile devices for accomplishing large-scale sensing tasks. Incentivizing device owners to contribute high-quality sensing data is a prerequisite for...
The advances in wireless communication techniques, mobile cloud computing, automotive and intelligent terminal technology are driving the evolution of vehicle ad hoc networks into the Internet of Vehicles (IoV) paradigm. This leads to a change in the...
Large-scale crowd flow prediction is a critical task in urban management and public safety. However, achieving accurate and efficient prediction remains challenging. Most existing models overlook spatial heterogeneity, employing unified parameters to...
To collect data efficiently and reliably in Mobile Crowd Sensing (MCS), a Participant Service Ability Aware (PSAA) data collecting mechanism is proposed. First, participants select the best sensing task according to the task complexity and desired re...
Dense urban environments pose significant challenges when it comes to detecting and measuring crowd size due to their nature of being free-flow environments containing many dynamic factors. In this paper, we use a wireless sensor network (WSN) to per...
The Mobile Crowd-sensing Network is a novel cyber–physical–social network which has received great attention recently and can be used as a powerful tool to monitor the phenomenon of the field of interest. Due to the limited budget, how to...
We investigate emerging mobile crowd sensing (MCS) systems, in which new cloud-based platforms sequentially allocate homogenous sensing jobs to dynamically-arriving users with uncertain service qualities. Given that human beings are selfish in nature...
Mobile crowd sensing (MCS) is a new computing paradigm for the internet of things, and it is widely accepted as a powerful means to achieve urban-scale sensing and data collection. In the MCS campaign, the smart mobilephone users can detect their sur...
The influx of wearable sensor devices has influenced a new paradigm termed wearable health crowd-sensing (WHCS). WHCS enables wearable data collection through active sensing to provide health monitoring to users. Wearable sensing devices capture data...
Mobile crowd sensing (MCS) systems usually attract numerous participants with widely varying sensing costs and interest preferences to perform tasks, where accurate task assignment plays an indispensable role and also faces many challenges (e.g., how...
In the field of mobile crowd sensing (MCS), the traditional client–cloud architecture faces increasing challenges in communication and computation overhead. To address these issues, this paper introduces edge computing into the MCS system and p...
Modelling and simulation of social interaction and networks are of high interest in multiple disciplines and fields of application ranging from fundamental social sciences to smart city management. Future smart city infrastructures and management are...
With the coverage of sensor-rich smart devices (smartphones, iPads, etc.), combined with the need to collect large amounts of data, mobile crowd sensing (MCS) has gradually attracted the attention of academics in recent years. MCS is a new and promis...
Crowd-sensing-based localization is regarded as an effective method for providing indoor location-based services in large-scale urban areas. The performance of the crowd-sensing approach is subject to the poor accuracy of collected daily-life traject...
Mobile crowd sensing is an innovative and promising paradigm in the construction and perception of smart cities. However, multi-task allocation in real-world scenarios is a huge challenge. There are many unexpected factors in the execution of mobile...
Mobile crowd-sensing (MCS) is a well-known paradigm used for obtaining sensed data by using sensors found in smart devices. With the rise of more sensing tasks and workers in the MCS system, it is now essential to design an efficient approach for tas...
The inspection of bridge structural cracks is essential to the structural safety evaluation and could provide reference for preventive maintenance. The traditional bridge structure inspection methods rely heavily on trained engineers with professiona...
Using mobile crowd sourcing/sensing (MCS) noise monitoring can lead to false sound level reporting. The methods used for recruiting mobile phones in an area of interest vary from selecting full populations to randomly selecting a single phone. Other...
Nowadays, people choose to travel in their leisure time more frequently, but fixed predetermined tour routes can barely meet people’s personalized preferences. The needs of tourists are diverse, largely personal, and possibly have multiple constraint...
Vehicular sensor networks (VSNs) consist of vehicles equipped with various sensing devices, such as LiDAR. In a VSN, vehicles and/or roadside units (RSUs) can be organized into a vehicular cloud (VC) to enable the sharing of sensing and computational...
The Internet of things (IoT) comprises a huge collection of electronic devices connected to the Internet to ensure the dependable exchange of sensing information. It involves mobile workers (MWs) who perform various activities to support enormous onl...
Augmented reality is well known for extending the real world by adding computer-generated perceptual information and overlaid sensory information. In contrast, simulation worlds are commonly closed and rely on artificial sensory information generated...
The population is increasing rapidly, due to which the number of vehicles has increased, but the transportation system has not yet developed as development occurred in technologies. Currently, the lowest capacity and old infrastructure of roads do no...
The ability of road vehicles to efficiently execute different sensing tasks varies because of the heterogeneity in their sensing ability and trajectories. Therefore, the data collection sensing task, which requires tempo-spatial sensing data, becomes...
The creation of an automatic crowd estimation system capable of providing reliable, real-time estimates of human crowd sizes would be an invaluable tool for organizers of large-scale events, particularly so in the context of safety management. We des...
This paper introduces a possible architecture and discusses the research directions for the realization of the Cognitive Perceptual Internet (CPI), which is enabled by the convergence of wired and wireless communications, traditional sensor networks,...
The possibility of understanding the dynamics of human mobility and sociality creates the opportunity to re-design the way data are collected by exploiting the crowd. We survey the last decade of experimentation and research in the field of mobile Cr...
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Remote sensing, as well as the recent advancements of crowd sensing, along with novel and recent geospatial technologies, have great potential to explore and understand the relationships between our surroundings—in particular our urban and rural envi...
Mobile crowdsensing (MCS) systems rely on the collective contribution of sensor data from numerous mobile devices carried by participants. However, the open and participatory nature of MCS renders these systems vulnerable to adversarial attacks or da...
Mobile computing is one of the significant opportunities that can be used for various practical applications in numerous fields in real life. Due to inherent characteristics of ubiquitous computing, devices can gather numerous types of data that led...
As organizations are increasingly involving individuals across their boundaries in the generation of new knowledge, crowd involvement can also be beneficial to cultural heritage organizations. We argue that in an “Open Innovation in Science&rdq...
Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the c...
Infectious diseases, such as COVID-19, SARS, MERS, etc., have seriously endangered human safety, economy, and education. During the spread of epidemics, restricting the range of activities of personnel is one of the options for the prevention and tre...
In this paper, we propose a novel congested crowd counting network for crowd density estimation, i.e., the Adaptive Multi-scale Context Aggregation Network (MSCANet). MSCANet efficiently leverages the spatial context information to accomplish crowd d...
Roads play a crucial role in urban transportation by facilitating the movement of materials within a city. The condition of road surfaces, such as damage and road facilities, directly affects traffic flow and influences decisions related to urban tra...
At present, the COVID-19 pandemic still presents with outbreaks occasionally, and pedestrians in public areas are at risk of being infected by the viruses. In order to reduce the risk of cross-infection, an advanced pedestrian state sensing method fo...
In Mobile Crowd Sensing (MCS), the power of the crowd, jointly with the sensing capabilities of the smartphones they wear, provides a new paradigm for data sensing. Scenarios involving user behavior or those that rely on user mobility are examples wh...
The rapid development of Multi-access Edge Computing (MEC) technology is transforming traditional platform services and enabling realization of the mMTC vision of 5G networks. MEC allows computational tasks to be offloaded to devices at the network e...
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