Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A Reference Survey

Growing progress in sensor technology has constantly expanded the number and range of low-cost, small, and portable sensors on the market, increasing the number and type of physical phenomena that can be measured with wirelessly connected sensors. Large-scale deployments of wireless sensor networks (WSN) involving hundreds or thousands of devices and limited budgets often constrain the choice of sensing hardware, which generally has reduced accuracy, precision, and reliability. Therefore, it is challenging to achieve good data quality and maintain error-free measurements during the whole system lifetime. Self-calibration or recalibration in ad hoc sensor networks to preserve data quality is essential, yet challenging, for several reasons, such as the existence of random noise and the absence of suitable general models. Calibration performed in the field, without accurate and controlled instrumentation, is said to be in an uncontrolled environment. This paper provides current and fundamental self-calibration approaches and models for wireless sensor networks in uncontrolled environments

A Method for Clustering and Cooperation in Wireless Multimedia Sensor Networks

Wireless multimedia sensor nodes sense areas that are uncorrelated to the areas covered by radio neighbouring sensors. Thus, node clustering for coordinating multimedia sensing and processing cannot be based on classical sensor clustering algorithms. This paper presents a clustering mechanism for Wireless Multimedia Sensor Networks (WMSNs) based on overlapped Field of View (FoV) areas. Overlapping FoVs in dense networks cause the wasting of power due to redundant area sensing. The main aim of the proposed clustering method is energy conservation and network lifetime prolongation. This objective is achieved through coordination of nodes belonging to the same cluster to perform assigned tasks in a cooperative manner avoiding redundant sensing or processing. A paradigm in this concept, a cooperative scheduling scheme for object detection, is presented based on the proposed clustering method

Game theory framework for MAC parameter optimization in energy-delay constrained sensor networks

Optimizing energy consumption and end-to-end (e2e) packet delay in energy-constrained, delay-sensitive wireless sensor networks is a conflicting multiobjective optimization problem. We investigate the problem from a game theory perspective, where the two optimization objectives are considered as game players. The cost model of each player is mapped through a generalized optimization framework onto protocol-specific MAC parameters. From the optimization framework, a game is first defined by the Nash bargaining solution (NBS) to assure energy consumption and e2e delay balancing. Secondy, the Kalai-Smorodinsky bargaining solution (KSBS) is used to find an equal proportion of gain between players. Both methods offer a bargaining solution to the duty-cycle MAC protocol under different axioms. As a result, given the two performance requirements (i.e., the maximum latency tolerated by the application and the initial energy budget of nodes), the proposed framework allows to set tunable system parameters to reach a fair equilibrium point that dually minimizes the system latency and energy consumption. For illustration, this formulation is applied to six state-of-the-art wireless sensor network (WSN) MAC protocols: B-MAC, X-MAC, RI-MAC, SMAC, DMAC, and LMAC. The article shows the effectiveness and scalability of such a framework in optimizing protocol parameters that achieve a fair energy-delay performance trade-off under the application requirements

Energy efficiency of MAC protocols in low data rate wireless multimedia sensor networks: A comparative study

Some new application scenarios for Wireless Sensor Networks (WSNs) such as urban resilience, smart house/building, smart agriculture and animal farming, among others, can be enhanced by adding multimedia sensors able to capture and transmit small multimedia samples such as still images or audio files. In these applications, Wireless Multimedia Sensor Networks (WMSNs) usually share two conflicting design goals. On the one hand, the goal of maximizing the network lifetime by saving energy, and on the other, the ability to successfully deliver packets to the sink. In this paper, we investigate the suitability of several WSNs MAC protocols from different categories for low data rate WMSNs by analyzing the effect of some network parameters, such as the sampling rate and the density of multimedia sensors on the energy consumption of nodes. First, we develop a general multi-class traffic model that allows us to integrate different types of sensors with different sampling rates. Then, we model, evaluate and compare the energy consumption of MAC protocols numerically. We illustrate how the MAC protocols put some constraints on network parameters like the sampling rates, the number of nodes, the size of the multimedia sample and the density of multimedia nodes in order to make collisions negligible and avoid long queuing delays. Numerical results show that in asynchronous MAC protocols, the receiver-initiated MAC protocols (RI-MAC and PW-MAC) consume less energy than the sender-initiated ones (B-MAC and X-MAC). B-MAC outperforms X-MAC when the sampling rates of multimedia nodes is very low and the polling periods are short. PW-MAC shows the lowest energy consumption between the selected asynchronous MAC protocols and it can be used in the considered WMSNs with a wider range of sampling rates. Regarding synchronous MAC protocols, results also show that they are only suitable for the considered WMSNs when the data rates are very low. In that situation, TreeMAC is the one that offers the lowest energy consumption in comparison to L-MAC and T-MAC. Finally, we compare the energy consumption of MAC protocols in four selected application scenarios related to Smart Cities and environment monitoring

H2020 project CAPTOR dataset: Raw data collected by low-cost MOX ozone sensors in a real air pollution monitoring network

The H2020 CAPTOR project deployed three testbeds in Spain, Italy and Austria with low-cost sensors for the measurement of tropospheric ozone (O3). The aim of the H2020 CAPTOR project was to raise public awareness in a project focused on citizen science. Each testbed was supported by an NGO in charge of deciding how to raise citizen awareness according to the needs of each country. The data presented in this document correspond to the raw data captured by the sensor nodes in the Spanish testbed using SGX Sensortech MICS 2614 metal-oxide sensors. The Spanish testbed consisted of the deployment of twenty-five nodes. Each sensor node included four SGX Sensortech MICS 2614 ozone sensors, one temperature sensor and one relative humidity sensor. Each node underwent a calibration process by co-locating the node at an EU reference air quality monitoring station, followed by a deployment in a sub-urban or rural area in Catalonia, Spain. All nodes spent two to three weeks co-located at a reference station in Barcelona, Spain (urban area), followed by two to three weeks co-located at three sub-urban reference stations near the final deployment site. The nodes were then deployed in volunteers' homes for about two months and, finally, the nodes were co-located again at the sub-urban reference stations for two weeks for final calibration and assessment of potential drifts. All data presented in this paper are raw data taken by the sensors that can be used for scientific purposes such as calibration studies using machine learning algorithms, or once the concentration values of the nodes are obtained, they can be used to create tropospheric ozone pollution maps with heterogeneous data sources (reference stations and low-cost sensors)