A suitable sampling technology to identify species and to estimate population dynamics based on individual counts at different temporal levels in relation to habitat variations is increasingly important for fishery management and biodiversity studies. In the past two decades, as interest in exploring the oceans for valuable resources and in protecting these resources from overexploitation have grown, the number of cabled (permanent) submarine multiparametric platforms with video stations has increased. Prior to the development of seafloor observatories, the majority of autonomous stations were battery powered and stored data locally. The recently installed low-cost, multiparametric, expandable, cabled coastal Seafloor Observatory (OBSEA), located 4 km off of Vilanova i la Gertrú, Barcelona, at a depth of 20 m, is directly connected to a ground station by a telecommunication cable; thus, it is not affected by the limitations associated with previous observation technologies. OBSEA is part of the European Multidisciplinary Seafloor Observatory (EMSO) infrastructure, and its activities are included among the Network of Excellence of the European Seas Observatory NETwork (ESONET). OBSEA enables remote, long-term, and continuous surveys of the local ecosystem by acquiring synchronous multiparametric habitat data and bio-data with the following sensors: Conductivity-Temperature-Depth (CTD) sensors for salinity, temperature, and pressure; Acoustic Doppler Current Profilers (ADCP) for current speed and direction, including a turbidity meter and a fluorometer (for the determination of chlorophyll concentration); a hydrophone; a seismometer; and finally, a video camera for automated image analysis in relation to species classification and tracking. Images can be monitored in real time, and all data can be stored for future studies. In this article, the various components of OBSEA are described, including its hardware (the sensors and the network of marine and land nodes), software (data acquisition, transmission, processing, and storage), and multiparametric measurement (habitat and bio-data time series) capabilities. A one-month multiparametric survey of habitat parameters was conducted during 2009 and 2010 to demonstrate these functions. An automated video image analysis protocol was also developed for fish counting in the water column, a method that can be used with cabled coastal observatories working with still images. Finally, bio-data time series were coupled with data from other oceanographic sensors to demonstrate the utility of OBSEA in studies of ecosystem dynamics.

The study of the effects of climate change on the marine environment requires the existence of sufficiently long time series of key parameters. The study of these series allows both to characterize the range of variability in each particular region and to detect trends or changes that could be attributed to anthropogenic causes. For this reason, networks of permanent cabled observation systems are being deployed in the ocean. This paper presents a balance of a decade of activity at the OBSEA cabled observatory, as an example of ocean monitoring success and drawbacks. It is not the objective of this article to analyze the scientific and technical aspects already presented by the authors in different publications (Table 4). We will evaluate the overall experience by retracing the different steps of infrastructure deployment and maintenance, focusing on routines for in situ control, damages experienced, breakdowns and administrative constraints by local administrations. We will conclude by providing a set of guidelines to improve cabled observatories scientific outreach, societal projection, and economic efficiency. As a result of this work, a 10-years dataset has been published in Pangaea that is available for the community [1], [2].

A novel Kinetic Energy Harvester (KEH) has been developed for powering oceanic undrogued drifters. It consists on a double pendulum system capable of transforming the wave oscillations into rotation on a flywheel. This rotation is converted into DC current by an electrical generator and further processed by a power management unit (PMU). The PMU includes a “maximum power point tracking” system to maximize energy production by the generator. An oceanic drifter has also been designed to embed the KEH and a custom-made measurement system to perform real sea tests. It counts on an Inertial Measurement Unit to study the motion of the drifter and an embedded measurement system to estimate the rotation speed of the generator and the power at both the input and output of the PMU. A Wi-Fi connection is also included for data transfer at short distances. The generator was firstly characterized at the laboratory; the drifter was then placed on a linear shaker to assess its performance. Finally, the drifter was deployed in a controlled sea area with average values of wave height and frequency of 1.43 m and 0.29 Hz, respectively. In these conditions, the drifter showed horizontal and vertical oscillations with peak-to-peak accelerations of 0.8 g and power spectra centered around 1.5 Hz and 1 Hz, respectively. As a result, the KEH generated a mean output power of 0.18 mW, with peaks of 2.5 mW.

Multiparametric video-cabled marine observatories are becoming strategic to monitor remotely and in real-time the marine ecosystem. Those platforms can achieve continuous, high-frequency and long-lasting image data sets that require automation in order to extract biological time series. The OBSEA, located at 4 km from Vilanova i la Geltrú at 20 m depth, was used to produce coastal fish time series continuously over the 24-h during 2013–2014. The image content of the photos was extracted via tagging, resulting in 69917 fish tags of 30 taxa identified. We also provided a meteorological and oceanographic dataset filtered by a quality control procedure to define real-world conditions affecting image quality. The tagged fish dataset can be of great importance to develop Artificial Intelligence routines for the automated identification and classification of fishes in extensive time-lapse image sets.

Effective ocean and coastal data management are needed to manage marine ecosystem health. Past ocean and coastal data management systems were often very specific to a particular application and region, but this focused approach often lacks real-time data and sharing/interoperating capability. The challenge for the ocean observing community is to devise standards and practices that enable integration of data from sensors across devices, manufacturers, users, and domains to enable new types of applications and services that facilitate much more comprehensive understanding and analyses of marine ecosystem. A given kind of sensor may be deployed on various platforms such as floats, gliders or moorings, and thus must be integrated with different operation, and data management systems. Simplifying the integration process in existing or newly established observing systems would benefit system operators and is important for the broader application of diverse sensors. This paper describes a geospatial “sensor web” architecture developed by the “NeXOS” project for ocean and coastal data management, based on the concepts of spatial data infrastructure and the Sensor Web Enablement framework of the Open Geospatial Consortium. This approach reduces the effort to propagate data from deployed sensors to users. To support the realization of the proposed Next generation Ocean Sensors (NeXOS) architecture, hardware and software specifications for a Smart Electronic Interface for Sensors and Instruments (SEISI) are described. SEISI specifies small lower-power electronics, minimal operating system, and standards-basedresearch software to enable web-based sharing, discovery, exchange, and processing of sensor observations as well as operation of sensor devices. An experimental scenario is presented in which sensor data from a low-power glider with low-bandwidth intermittent satellite communications is integrated into the geospatial sensor web using the NeXOS architecture.

The Ocean Bottom Seismometer (OBS) is a key instrument for the geophysical study of sea sub-bottom layers. At present, more reliable autonomous instruments capable of recording underwater for long periods of time and therefore handling large data storage are needed. This paper presents a new Ocean Bottom Seismometer designed to be used in long duration seismic surveys. Power consumption and noise level of the acquisition system are the key points to optimize the autonomy and the data quality. To achieve our goals, a new low power data logger with high resolution and Signal–to-Noise Ratio (SNR) based on Compact Flash memory card is designed to enable continuous data acquisition. The equipment represents the achievement of joint work from different scientific and technological disciplines as electronics, mechanics, acoustics, communications, information technology, marine geophysics, etc. This easy to handle and sophisticated equipment allows the recording of useful controlled source and passive seismic data, as well as other time varying data, with multiple applications in marine environment research. We have been working on a series of prototypes for ten years to improve many of the aspects that make the equipment easy to handle and useful to work in deep-water areas. Ocean Bottom Seismometers (OBS) have received growing attention from the geoscience community during the last forty years. OBS sensors recording motion of the ocean floor hold key information in order to study offshore seismicity and to explore the Earth’s crust. In a seismic survey, a series of OBSs are placed on the seabed of the area under study, where they record either natural seismic activity or acoustic signals generated by compressed air-guns on the ocean surface. The resulting data sets are subsequently used to model both the earthquake locations and the crustal structure.