The sustainable management of coastal and offshore ecosystems, such as for example coral reef environments, requires the collection of accurate data across various temporal and spatial scales. Accordingly, monitoring systems are seen as central tools for ecosystem-based environmental management, helping on one hand to accurately describe the water column and substrate biophysical properties, and on the other hand to correctly steer sustainability policies by providing timely and useful information to decision-makers. A robust and intelligent sensor network that can adjust and be adapted to different and changing environmental or management demands would revolutionize our capacity to wove accurately model, predict, and manage human impacts on our coastal, marine, and other similar environments. In this paper advanced evolutionary techniques are applied to optimize the design of an innovative energy harvesting device for marine applications. The authors implement an enhanced technique in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches, Particle Swarm Optimization and Genetic Algorithms. Here, this hybrid procedure is applied to a power buoy designed for marine environmental monitoring applications in order to optimize the recovered energy from sea-wave, by selecting the optimal device configuration.
Wireless sensor netwoks (WSN) employ miniaturized devices which integrate sensing, processing, and communication capabilities. In this paper an innovative mobile platform for heterogeneous sensor networks is presented, combined with adaptive methods to optimize the communication architecture for novel potential applications even in coastal and marine environment monitoring. In fact, in the near future, WSN data collection could be performed by UAV platforms which can be a sink for ground sensors layer, acting essentially as a mobile gateway. In order to maximize the system performances and the network lifespan, the authors propose a recently developed hybrid technique based on evolutionary algorithms. This procedure is here applied to optimize the communication energy consumption in WSN by selecting the optimal multi-hop routing schemes, with a suitable hybridization of different routing criteria. The proposed approach can be potentially extended and applied to ongoing research projects focused on UAV-based remote sensing of the ocean, sea ice, coastal waters, and large water regions.
Sensor networks are an emerging field of research which presents significant system challenges involving the
use of large numbers of resource-constrained nodes operating essentially unattended and exposed to potential
local communication failures. Current sensor networks address problems of meeting standards for accuracy and
also delivering data from remote locations with an appropriate level of spatial and temporal resolution. Today
advances in sensor technology, wireless communications and digital electronics make it possible to produce
large amount of small-size, low-cost sensors which integrate together sensing, processing, and communication
capabilities. The advantages are evident not only in the reduction of size, but also in the increase of functional
performance and reliability, and a unit-cost reduction in mass production lines. In this work hybrid evolutionary
algorithms are applied to optimize the design of cluster formation in wireless sensor networks, guaranteeing at
the same time a full network connectivity and a minimum energy consumption. The proposed techniques have
been tested in respect of the most known test functions with good results obtained in all the considered cases,
especially for optimization of large domain objective functions. This feature makes these algorithms suitable for
a wide range of applications, capable of outperforming classical procedures.
The increasing need to manage complex environmental problems demands a new approach and new technologies
to provide the information required at a spatial and temporal resolution appropriate to the scales at which the
biological processes occur. In particular sensor networks, now quite popular on land, still poses many difficult
problems in underwater environments. In this context, it is necessary to develop an autonomous monitoring
system that can be remotely interrogated and directed to address unforeseen or expected changes in such environmental
conditions. This system, at the highest level, aims to provide a framework for combining observations
from a wide range of different in-situ sensors and remote sensing instruments, with a long-term plan for how
the network of sensing modalities will continue to evolve in terms of sensing modality, geographic location, and
spatial and temporal density. The advances in sensor technology and digital electronics have made it possible
to produce large amount of small tag-like sensors which integrate sensing, processing, and communication
capabilities together and form an autonomous entity. To successfully use this kind of systems in under water
environments, it becomes necessary to optimize the network lifetime and face the relative hindrances that such
a field imposes, especially in terms of underwater information exchange.
The sustainable management of coastal and offshore ecosystems, such as coral reef environments, requires the collection of accurate data across various temporal and spatial scales. Accordingly, monitoring systems are seen as central tools for ecosystem-based environmental management, helping on one hand to accurately describe the water column and substrate biophysical properties, and on the other hand to correctly steer sustainability policies by providing timely and useful information to decision-makers. A robust and intelligent sensor network that can adjust and be adapted to different and changing environmental or management demands would revolutionize our capacity to wove accurately model, predict, and manage human impacts on our coastal, marine, and other environments. Underwater measurements are greatly influenced by environmental conditions; especially in shallow waters. Temperature, salinity, turbidity, oxygen, pH and many other parameters still need optimization due to the difficulty in performing the process <i>in situ</i> in such an environment. Notably however, modern developments in wireless network technology and miniaturization now make it possible to realistically monitor the aquatic environment <i>in situ</i> using smart devices that are completely autonomous. However, to successfully use these kinds of systems in under water environments it is necessary from the outset to define the specific requirements and relative hindrances that such a field imposes; especially in terms of underwater information exchange. The aim of this paper is to examine these issues and to propose strategies for the cost effective and scientifically robust integration of remote sensor network technologies for the monitoring and management of critical marine environments such as coral reefs.
Sensor packaging has been identified as one of the most significant areas of research for enabling sensor usage in harsh environments for several application fields. Protection is one of the primary goals of sensor packaging; however, research deals not only with robust and resistant packages optimization, but also with electromagnetic performance. On the other hand, from the economic point of view, wireless sensor networks present hundreds of thousands of small sensors, namely motes, whose costs should be reduced at the lowest level, thus driving low the packaging cost also. So far, packaging issues have not been extended to such topics because these products are not yet in the advanced production cycle. However, in order to guarantee high EMC performance and low packaging costs, it is necessary to address the packaging strategy from the very beginning. Technological improvements that impacts on production time and costs can be suitable organized by anticipating the above mentioned issues in the development and design of the motes, obtaining in this way a significant reduction of final efforts for optimization. The paper addresses the development and production techniques necessary to identify the real needs in such a field and provides the suitable strategies to enhance industrial performance of high-volumes productions. Moreover the electrical and mechanical characteristics of these devices are reviewed and better identified in function of the environmental requirements and electromagnetic compatibility. Future developments complete the scenario and introduce the next mote generation characterized by a cost lower by an order of magnitude.
Microelectronics for environmental monitoring (microsensors, etc.) present a variety of power supply voltages and operative frequencies from one side and are subject to interference and noise from the external environment on the other. All these aspects lead accuracy and reliability of those circuits devoted to physical measurements a difficult compromise for the designer. Sensors implemented in the newest generation of networks are realized by integrating advanced analog features with digital processing capabilities. The analog blocks, above all, where the processing related to the signal provided by the active element is performed, show in the most substantial way this problem related to EMC inadequacy. In order to restore the top-quality features it is necessary to arrange the best shielding design for the blocks more influenced by interference and noise. So the work of the designer leads to the analysis, simulation and realization of localized and global shields inside and on the packaging. The problem related to the definition of EMC role in designing such shields is very substantial for environmental applications, where performance leads to improve and optimize the traditional designing techniques. The proposal and consequent application of general criteria devoted to define specific needs for shielding is the first step of a logical development oriented to the mature industrial production of efficient and reliable devices able to maintain their performance independently by the influence of external and internal noise.
EBG structures are typically two or three dimensional periodic media characterized by the capability to inhibit the electromagnetic wave propagation for each angle and each polarization in a specific frequency band. These complex structures present different degrees of freedom, that can be used to optimize the performances of the application. On the other hand, the management of different degrees of freedom can result in the increasing of the complexity in the entire device-design procedure. The aim of this research is to analyse the optimization of EBG materials by means of a new technique: the Genetical Swarm Optimization (GSO). This approach consists of a co-operation of GA and PSO. The GSO results in a fast method for optimization of complex nonlinear objective functions and its wider potential makes it suitable for every electromagnetic applications. These optimized synthetic materials can represent an opportunity for the development and design of innovative electromagnetic devices.