A New Coastal Crawler Prototype to Expand the Ecological Monitoring Radius of OBSEA Cabled Observatory

The use of marine cabled video observatories with multiparametric environmental data collection capability is becoming relevant for ecological monitoring strategies. Their ecosystem surveying can be enforced in real time, remotely, and continuously, over consecutive days, seasons, and even years. Unfortunately, as most observatories perform such monitoring with fixed cameras, the ecological value of their data is limited to a narrow field of view, possibly not representative of the local habitat heterogeneity. Docked mobile robotic platforms could be used to extend data collection to larger, and hence more ecologically representative areas. Among the various state-of-the-art underwater robotic platforms available, benthic crawlers are excellent candidates to perform ecological monitoring tasks in combination with cabled observatories. Although they are normally used in the deep sea, their high positioning stability, low acoustic signature, and low energetic consumption, especially during stationary phases, make them suitable for coastal operations. In this paper, we present the integration of a benthic crawler into a coastal cabled observatory (OBSEA) to extend its monitoring radius and collect more ecologically representative data. The extension of the monitoring radius was obtained by remotely operating the crawler to enforce back-and-forth drives along specific transects while recording videos with the onboard cameras. The ecological relevance of the monitoring-radius extension was demonstrated by performing a visual census of the species observed with the crawler’s cameras in comparison to the observatory’s fixed cameras, revealing non-negligible differences. Additionally, the videos recorded from the crawler’s cameras during the transects were used to demonstrate an automated photo-mosaic of the seabed for the first time on this class of vehicles. In the present work, the crawler travelled in an area of 40 m away from the OBSEA, producing an extension of the monitoring field of view (FOV), and covering an area approximately 230 times larger than OBSEA’s camera. The analysis of the videos obtained from the crawler’s and the observatory’s cameras revealed differences in the species observed. Future implementation scenarios are also discussed in relation to mission autonomy to perform imaging across spatial heterogeneity gradients around the OBSEA

Colorado water, November/December 2018

The newsletter is devoted to highlighting water research and activities at CSU and throughout Colorado.Newsletter of the Colorado Water Center. Theme: Irrigation innovation and technology

United States Air Force Applications of Unmanned Aerial Systems: Modernizing Airfield Damage Assessment

Modernizing airfield damage assessment has long been a priority mission at the Air Force Civil Engineer Center (AFCEC). Previously, AFCEC has made advances to expedite unexploded ordnance (UXO) neutralization and pavement repair. Missing from these initiatives is the initial assessment component. This thesis expands the idea of using Small Unmanned Aerial Systems (SUAS), applies it to the Air Force mission, and provides SUAS vehicle configuration and sensor recommendations. In this study, 25 civil engineer officers reviewed airfield imagery gathered using two small air vehicles. For the first review, participants attempted to identify UXOs and foreign object debris (FOD) in a computer interface that leverages images collected by a fixed-wing air vehicle. The second review uses a two-dimensional map created using a hex-rotor. The results of both systems were then compared to the status quo. Resulting statistics indicate that, irrespective of image resolution, additional analysis time does not result in greater object detection or correct identification. Overall, this thesis concludes that SUAS use for afield damage assessment shows promise. Moreover, they can provide the Air Force improved precision for locating UXOs and FOD, as well as estimate dimensions of damage. Dedicating resources to developing this technology will also assist with improving object detection and manpower efficiency. Further research is required for optimal image characterization requisite for reducing and/or eliminating the occurrence of false negative events

Monitoring and Mapping Solutions Using Sensor Nodes and Drones

Researchers are always looking for innovative ways to collect the environmental data and ease the process of data collection on the field. Advancement in sensor technologies and drones has led to easy technological access to design custom solutions even with basic electronics and technical knowledge. This paper documents, construction and working of “ITT Smart Sense”, which is a low power, easy to use and cost effective environment monitoring system using wireless sensor network that runs autonomously on battery power for an extended period of time. Along with that, a UAV based platform, titled “ITT Smart Sense Fly”, focused on environmental monitoring and scientific research and is tailored to the needs of researchers has been proposed in this paper. This platform is comprised of an autonomous unmanned aerial vehicle (UAV)/Drone with a camera sensor, an autopilot mobile app for mission planning and other required Photogrammetry tools. The drone navigates over the area of interest based on a pre-programmed flight plan and captures a series of photographs using the on-board camera. The collected image data set is processed to create orthomosaics, high resolution maps and 3D point cloud. The proposed solutions were demonstrated with three distinct case studies

The Design Fabrication and Flight Testing of an Academic Research Platform for High Resolution Terrain Imaging

This thesis addresses the design, construction, and flight testing of an Unmanned Aircraft System (UAS) created to serve as a testbed for Intelligence, Surveillance, and Reconnaissance (ISR) research topics that require the rapid acquisition and processing of high resolution aerial imagery and are to be performed by academic research institutions. An analysis of the requirements of various ISR research applications and the practical limitations of academic research yields a consolidated set of requirements by which the UAS is designed. An iterative design process is used to transition from these requirements to cycles of component selection, systems integration, flight tests, diagnostics, and subsystem redesign. The resulting UAS is designed as an academic research platform to support a variety of ISR research applications ranging from human machine interaction with UAS technology to orthorectified mosaic imaging. The lessons learned are provided to enable future researchers to create similar systems

Signals in the Soil: Subsurface Sensing

In this chapter, novel subsurface soil sensing approaches are presented for monitoring and real-time decision support system applications. The methods, materials, and operational feasibility aspects of soil sensors are explored. The soil sensing techniques covered in this chapter include aerial sensing, in-situ, proximal sensing, and remote sensing. The underlying mechanism used for sensing is also examined as well. The sensor selection and calibration techniques are described in detail. The chapter concludes with discussion of soil sensing challenges

CMOS active pixel sensor type imaging system on a chip

A single chip camera which includes an .[.intergrated.]. .Iadd.integrated .Iaddend.image acquisition portion and control portion and which has double sampling/noise reduction capabilities thereon. Part of the .[.intergrated.]. .Iadd.integrated .Iaddend.structure reduces the noise that is picked up during imaging

Utilization Of A Large-Scale Wireless Sensor Network For Intrusion Detection And Border Surveillance

To control the border more effectively, countries may deploy a detection system that enables real-time surveillance of border integrity. Events such as border crossings need to be monitored in real time so that any border entries can be noted by border security forces and destinations marked for apprehension. Wireless Sensor Networks (WSNs) are promising for border security surveillance because they enable enforcement teams to monitor events in the physical environment. In this work, probabilistic models have been presented to investigate senor development schemes while considering the environmental factors that affect the sensor performance. Simulation studies have been carried out using the OPNET to verify the theoretical analysis and to find an optimal node deployment scheme that is robust and efficient by incorporating geographical coordination in the design. Measures such as adding camera and range-extended antenna to each node have been investigated to improve the system performance. A prototype WSN based surveillance system has been developed to verify the proposed approach