Abstract. This paper presents a mobile, low-cost particulate matter sensing approach for the use in Participatory Sensing scenarios. It shows that cheap commercial o-the-shelf (COTS) dust sensors can be used in distributed or mobile personal measurement devices at a cost one to two orders of magnitude lower than that of current hand-held solutions, while reaching meaningful accuracy. We conducted a series of experiments to juxtapose the performance of a gauged high-accuracy measurement device and a cheap COTS sensor that we tted on a Bluetooth-enabled sensor module that can be interconnected with a mobile phone. Calibration and processing procedures using multi-sensor data fusion are presented, that perform very well in lab situations and show practically relevant results in a realistic setting. An on-the-y calibration correction step is proposed to address remaining issues by taking advantage of co-located measurements in Participatory Sensing scenarios. By sharing few measurement across devices, a high measurement accuracy can be achieved in mobile urban sensing applications, where devices join in an ad-hoc fashion. A performance evaluation was conducted by co-locating measurement devices with a municipal measurement station that monitors particulate matter in a European city, and simulations to evaluate the on-the-y cross-device data processing have been done.

This work discusses ways of measuring particulate matter with mobile devices. Solutions using a dedicated sensor device are presented along with a novel method of retrofitting a sensor to a camera phone without need for electrical modifications. Instead, the flash and camera of the phone are used as light source and receptor of an optical dust sensor respectively. Experiments to evaluate the accuracy are presented.

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Abstract-Intelligent environments (IE) leverage embedded processing and wireless communication to assist users in a variety of ways. Applications rely on low power consumption for longer lifetimes, though different applications require different Qualityof-Service (QoS) requirements from the MAC layer. Until now, low power has come at the cost of other QoS parameters such as latency or packet loss. This paper presents WoR-MAC, a wireless MAC protocol which allows pre-existing protocols to be combined with remote multi-node wake-ups. The protocols are embedded into Wake-on-Radio (WoR) frames, allowing nodes to sleep during periods of low activity and be woken asynchronously with a single short RF signal. After waking, nodes begin communication using the embedded MAC protocol. Once the nodes have been woken, they maintain the QoS of the original MAC, with greatly reduced power consumption. The results indicate that WoR-MAC maintains packet loss characteristics of CSMA-CA and TDMA, as well as latency after accounting for the duty cycle and collaborative parameter estimation, while reducing power consumption by up to 49%, very close to the lower bound given by the duty-cycle.