# A Survey on Monitoring Quality Assessment for Wireless Visual Sensor Networks
## 1 Introduction  
Sensors-based applications have been largely employed to retrieve and process data in a distributed way. If those applications also incorporate data retrieving performed by visual sensor nodes, Wireless Visual Sensor Networks (WVSN) can be created [1, 2]. In short, a visual sensor node in a WVSN typically comprises a camera, a processing unit and a wireless transceiver, but the available processing power and the actual energy consumption will significantly differ among them, resulting in different hardware possibilities in this area. Whatever the case, visual sensor nodes will enable image and video data gathering and processing, allowing for the extraction of potential relevant information that might provide richer descriptions about monitored events in a modelled system [1, 3]. Nowadays, new approaches have emerged to harness the possibilities of visual monitoring based on multiple sources of sensors-based data. The prominent context of Internet of Things (IoT) has brought the wireless (visual) sensor networks scope closer to the Internet world, which have fostered new opportunities but also disclosed new challenges forvisual data processing. This fact has reinforced the need for efficient solutions, particularly considering specific high-demanding requirements when dealing with visual applications. Visual sensors-based networks may achieve a deeper perception of the monitored environment, leveraging the particularities of several monitoring applications [4], especially when they are operating over the Internet. Examples of such applications are surveillance [5], Industry 4.0 automation and control [6], smart street lighting [7], smart homes [8], smart grids [9], traffic and pedestrian control [10], living assistance [11], driving assistance [12], waste collection [13], emergency detection [14], among many others. For all those applications, it is fundamental to fulfill the _quality_ requirement associated with the monitoring tasks performance. However, the definition and evaluation of such quality is not straightforward, demanding a proper characterization regarding which network and application parameters should be considered and modelled with respect to quality of monitoring. In fact, for the proper execution of the mentioned applications, some defined tasks must to be executed as good as possible, although the definition of \"good\" may be vague in many contexts. However, it is reasonable to expect that the defined tasks will have some minimum acceptable quality level that have to be attended. Frequently, such minimum levels are associated with Quality of Service (QoS) or Quality of Experience (QoE) indicators, which can be easily associated with monitoring functions of sensor networks. In short, QoS can be expressed as the measured performance of a provided service, which in the context of WVSN is generally associated with capabilities of a network and associated functions. On the other hand, QoE focuses on user perceptions, experiences, and expectations, which is often associated with subjective components [15; 16]. However, other aspects may also impact on the outcome that a visual application delivers to the user, such as sharpness, power consumption, perspective, occlusion, spatial coverage, lifetime and dependability. Thus, quality evaluation has been a highly desired service that may be too complex to achieve though, demanding proper reasoning and adequate methods. A recurrent concern for WVSN has been the quality of the content of the visual data in terms of resolution (pixel density), definition (amount of information) and sharpness of an image. This means that a WVSN that gather sharper images, with more definition and higher resolution, may be assumed as having higher quality. On the other hand, such WVSN may consume more energy when pursing that quality level, somehow jeopardizing the overall quality perception of the application.