Abstract
Visual data monitoring in wireless sensor networks can significantly enrich a large set of surveillance and general purpose monitoring applications. However, transmission of image snapshots or video streams can rapidly deplete the energy resources of the deployed nodes, turning energy efficiency into a major optimization issue. During wireless transmissions, packets can be corrupted directly affecting the monitoring quality of the applications. One reasonable way to reduce quality loss is the transmission of redundant packets for higher error resilience, but additional packet transmissions may incur in undesirable energy consumption. Frequently, some monitoring quality loss may be tolerated since visual information retrieved from source nodes may have different relevance for the applications, according to the monitoring requirements and the current sensors' poses and fields of view. In such way, we propose that only high-relevant source nodes will transmit redundant packets, assuring error resilience only for the most relevant visual data for the monitoring application. Doing so, energy is saved over the network when fewer packets are transmitted in average, potentially enlarging the network lifetime with reduced impact to the overall monitoring quality. © 2013. WSEAS Transactions on Communications.

Abstract
The IEEE 802.15.4/ZigBee set of standards is one of the most used wireless sensor network technologies. This set of standards supports cluster-tree networks, which are suitable topologies for wide-scale deployments. The design of wide-scale wireless sensor networks is a challenging task because it is difficult to test, analyse and validate new designs in real scenarios. Thus, simulation becomes a convenient and feasible method for its assessment before deployment. Within this context, we provide a set of simulation models for IEEE 802.15.4/ZigBee-based networks, which are able to deal with wide-scale cluster-tree wireless sensor networks and to address their major challenges. The provided simulation models implement important mechanisms for the assessment of wide-scale cluster-tree networks and associated data communication mechanisms, enabling an easier design and test of wide-scale wireless sensor network implementations.

Abstract
The operation of Wireless Sensor Networks (WSNs) is subject to multiple constraints, among which one of the most critical is available energy. Sensor nodes are typically powered by electrochemical batteries. The stored energy in battery devices is easily influenced by the operating temperature and the discharge current values. Therefore, it becomes difficult to estimate their voltage/charge behavior over time, which are relevant variables for the implementation of energy-aware policies. Nowadays, there are hardware and/or software approaches that can provide information about the battery operating conditions. However, this type of hardware-based approach increases the battery production cost, which may impair its use for sensor node implementations. The objective of this work is to propose a software-based approach to estimate both the state of charge and the voltage of batteries in WSN nodes based on the use of a temperature-dependent analytical battery model. The achieved results demonstrate the feasibility of using embedded analytical battery models to estimate the lifetime of batteries, without affecting the tasks performed by the WSN nodes.

Abstract
Energy consumption is a major concern in Wireless Sensor Networks (WSNs) since nodes are powered by batteries. Usually, batteries have low capacity and can not be replaced due to economic and/or logistical issues. In addition, batteries are complex devices as they depend on electrochemical reactions to generate energy. As a result, batteries exhibit non-linear behaviour over time, which makes difficult to estimate their lifetime. Analytical battery models are abstractions that allow estimating the battery lifetime through mathematical equations, taking into account important effects such as rate capacity and charge recovery. The recovery effect is very important since it enables charge gains in the battery after its electrochemical stabilization. Sleep scheduling approaches may take advantage of the recovery effect by adding sleep periods in the node activities in order to extend the network lifetime. This work aims to analyse the recovery effect within WSN context, particularly regarding low-power nodes. To do so, we use an analytical battery model for analysing the battery performance over time, during the node execution. © Springer International Publishing AG 2017.

Abstract
Wireless sensor networks are an emerging technology that can provide valuable information for a large series of monitoring and control applications. Comprising many monitoring scenarios with different particularities, as industrial management, weather forecasting, home automation, traffic management and rescue operations, just to cite a few, wireless sensor networks bring many possibilities for innovative applications that cannot be addressed by conventional wireless network technologies. When sensors are equipped with cameras or microphones, multimedia data can be retrieved from the monitored field, enriching the perception of the target area. However, the constrained nature of wireless sensor networks imposes many challenges to multimedia transmission, fostering development of optimized protocols. In this chapter, we present the state of the art of multimedia transmission in wireless sensor networks, covering topics as routing, error control, congestion avoidance, real-time delivery, compression and QoS, potentially supporting in the development of wireless multimedia sensor networks.

Abstract
Many Wireless Sensor Network (WSN) applications operate autonomously in unreliable or inaccessible environments, precluding maintenance or human intervention. Redundant deployment schemes are usually considered in this scenario, making the network resilient to failure and environmental changes. Furthermore, sleep-scheduling techniques can also be applied, enabling redundant nodes to turn off their radios, while active nodes perform monitoring services. This paper investigates the behavior of the (m,k)-Gur Game approach. The main goal of the (m,k)-Gur Game is to provide an uniform network coverage for monitoring applications, with autonomic nodes performing a self-regulated choice between sending message to a base station or sleep until the next period. The proposal was evaluated using the OMNeT++ simulator tool under the MiXiM framework. Preliminary results shows that the (m,k)-Gur Game outperforms the traditional GurGame approach in terms of QoS provision and network coverage.