11,770 research outputs found
Integrative IRT for documentation and interpretation of archaeological structures
The documentation of built heritage involves tangible and intangible features. Several morphological and metric aspects of architectural structures are acquired throughout a massive data capture system, such as the Terrestrial Laser Scanner (TLS) and the Structure from Motion (SfM) technique. They produce models that give information about the skin of architectural organism. Infrared Thermography (IRT) is one of the techniques used to investigate what is beyond the external layer. This technology is particularly significant in the diagnostics and conservation of the built heritage. In archaeology, the integration of data acquired through different sensors improves the analysis and the interpretation of findings that are incomplete or transformed.
Starting from a topographic and photogrammetric survey, the procedure here proposed aims to combine the bidimensional IRT data together with the 3D point cloud. This system helps to overcome the Field of View (FoV) of each IRT image and provides a three-dimensional reading of the thermal behaviour of the object. This approach is based on the geometric constraints of the pair of RGB-IR images coming from two different sensors mounted inside a bi-camera commercial device. Knowing the approximate distance between the two sensors, and making the necessary simplifications allowed by the low resolution of the thermal sensor, we projected the colour of the IR images to the RGB point cloud. The procedure was applied is the so-called Nymphaeum of Egeria, an archaeological structure in the Caffarella Park (Rome, Italy), which is currently part of the Appia Antica Regional Park
Recommended from our members
Context-awareness for mobile sensing: a survey and future directions
The evolution of smartphones together with increasing computational power have empowered developers to create innovative context-aware applications for recognizing user related social and cognitive activities in any situation and at any location. The existence and awareness of the context provides the capability of being conscious of physical environments or situations around mobile device users. This allows network services to respond proactively and intelligently based on such awareness. The key idea behind context-aware applications is to encourage users to collect, analyze and share local sensory knowledge in the purpose for a large scale community use by creating a smart network. The desired network is capable of making autonomous logical decisions to actuate environmental objects, and also assist individuals. However, many open challenges remain, which are mostly arisen due to the middleware services provided in mobile devices have limited resources in terms of power, memory and bandwidth. Thus, it becomes critically important to study how the drawbacks can be elaborated and resolved, and at the same time better understand the opportunities for the research community to contribute to the context-awareness. To this end, this paper surveys the literature over the period of 1991-2014 from the emerging concepts to applications of context-awareness in mobile platforms by providing up-to-date research and future research directions. Moreover, it points out the challenges faced in this regard and enlighten them by proposing possible solutions
Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations
As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance
An Autonomous Surface Vehicle for Long Term Operations
Environmental monitoring of marine environments presents several challenges:
the harshness of the environment, the often remote location, and most
importantly, the vast area it covers. Manual operations are time consuming,
often dangerous, and labor intensive. Operations from oceanographic vessels are
costly and limited to open seas and generally deeper bodies of water. In
addition, with lake, river, and ocean shoreline being a finite resource,
waterfront property presents an ever increasing valued commodity, requiring
exploration and continued monitoring of remote waterways. In order to
efficiently explore and monitor currently known marine environments as well as
reach and explore remote areas of interest, we present a design of an
autonomous surface vehicle (ASV) with the power to cover large areas, the
payload capacity to carry sufficient power and sensor equipment, and enough
fuel to remain on task for extended periods. An analysis of the design and a
discussion on lessons learned during deployments is presented in this paper.Comment: In proceedings of MTS/IEEE OCEANS, 2018, Charlesto
Cyber-Physical Systems for Smart Water Networks: A Review
There is a growing demand to equip Smart Water Networks (SWN) with advanced sensing and computation capabilities in order to detect anomalies and apply autonomous event-triggered control. Cyber-Physical Systems (CPSs) have emerged as an important research area capable of intelligently sensing the state of SWN and reacting autonomously in scenarios of unexpected crisis development. Through computational algorithms, CPSs can integrate physical components of SWN, such as sensors and actuators, and provide technological frameworks for data analytics, pertinent decision making, and control. The development of CPSs in SWN requires the collaboration of diverse scientific disciplines such as civil, hydraulics, electronics, environment, computer science, optimization, communication, and control theory. For efficient and successful deployment of CPS in SWN, there is a need for a common methodology in terms of design approaches that can involve various scientific disciplines. This paper reviews the state of the art, challenges, and opportunities for CPSs, that could be explored to design the intelligent sensing, communication, and control capabilities of CPS for SWN. In addition, we look at the challenges and solutions in developing a computational framework from the perspectives of machine learning, optimization, and control theory for SWN.acceptedVersio
- …