The advent of pervasive wireless systems faces several challenges due to the massive data traffic growth resulting from the interconnection of billions of new devices. This makes it essential to provide smart decision-making in identifying available ...

As interest in autonomous driving and advanced driver-assistance systems (ADAS) has grown, various sensing technologies have been developed to accurately determine the position and situation of surrounding vehicles and objects. In particular, light ...

Fully autonomous driving applications rely on a complete knowledge of their operational environment to ensure safety while maintaining efficient driving. However, in scenarios with close visual restrictions, such as urban traffic, the lack of sensor ...

This is a position paper that discusses the challenges of emerging new sensing modalities for both device-free and wearable sensing systems, as well as opportunities lying in the combination of them across multiple information scales. With the ...

Vehicular CrowdSensing (VCS) is an emerging solution designed to remotely collect data from smart vehicles. It enables a dynamic and large-scale phenomena monitoring just by exploring the variety of technologies which have been embedded in modern cars. ...

Wearable and connected health is a dominant field in the era of the Internet of Things (IoT). Indeed, Body Sensor Networks (BSNs) have been widely used for enabling many connected health applications in diverse areas including: activity recognition, ...

In this study, the authors investigate the energy‐aware quality of information (QoI) maximisation problem by jointly optimising the sensor selection, sampling rate, packet‐dropped rate, and transmit power in wireless sensor networks. By introducing the ...

Collaborative sensing has become increasingly popular in cognitive radio networks to enable unlicensed secondary users to coexist with the licensed primary users and share spectrum without interference. Despite its promise in performance enhancement, ...

In this paper, we consider a collaborative sensing scenario where sensing nodes are powered by energy harvested from the ambient environment. In each time slot, an active sensor consumes one unit amount of energy to take an observation and transmit it ...

Mobile phones include a variety of sensors that can be used to develop context-aware applications and gather data about the user's behavior, including the places he visits, his level of activity and how frequently and with whom he socializes. The ...

We introduce CoSense, a collaborative sensing platform for mobile devices that opportunistically distributes sensing tasks between familiar devices in close proximity. We use empirical energy measurements together with data collected from everyday ...

This paper studies mobile sensing in a complete distributed and opportunistic scheme. We present a novel sensing strategy for sensing nodes without movement constraints. This strategy offers information sharing and sensor scheduling that maximizes the ...

Crowdsourcing has inspired a variety of novel mobile applications. However, identifying common practices across different applications is still challenging. In this paper, we use smart parking as a case study to investigate features of crowdsourcing ...

Human mobility has been widely studied for a variety of purposes, from urban planning to the study of spread of diseases. These studies depend heavily on large datasets, and recent advances in collaborative sensing and WiFi infrastructures have created ...

Accelerometer data on a user's mobile phone contains abundant information that can be employed for user activity recognition. However, the existing schemes cannot provide accurate inference results under moving environments (e.g. on a train). This is ...

This paper introduces a Bayesian framework to detect multiple signals embedded in noisy observations, from an array of sensors. For various states of knowledge on the communication channel and the noise at the receiving sensors, a marginalization ...

The paper develops an ad hoc network of active pan/tilt/zoom (PTZ) and passive wide field-of-view (FOV) cameras capable of carrying out observation tasks autonomously. The network is assumed to be uncalibrated, lacks a central controller, and relies ...

Sensor networks have been conventionally defined as a network of sensor motes that collaboratively detect events and report them to a remote monitoring station. This paper makes an attempt to extend this notion to the social context by using mobile ...

Distributed Collaborative Adaptive Sensing (DCAS) of the atmosphere is a new paradigm for detecting and predicting hazardous weather using a dense network of short-range, low-powered radars to sense the lowest few kilometres of the earth's atmosphere. ...

Energy constraint is an important issue in wireless sensor networks. This paper proposes a distributed energy optimization method for target tracking applications. Sensor nodes are clustered by maximum entropy clustering. Then, the sensing field is ...