Real-time and post-processed georeferencing for hyperpspectral drone remote sensing

The use of drones and photogrammetric technologies are increasing rapidly in different applications. Currently, drone processing workflow is in most cases based on sequential image acquisition and post-processing, but there are great interests towards real-time solutions. Fast and reliable real-time drone data processing can benefit, for instance, environmental monitoring tasks in precision agriculture and in forest. Recent developments in miniaturized and low-cost inertial measurement systems and GNSS sensors, and Real-time kinematic (RTK) position data are offering new perspectives for the comprehensive remote sensing applications. The combination of these sensors and light-weight and low-cost multi- or hyperspectral frame sensors in drones provides the opportunity of creating near real-time or real-time remote sensing data of target object. We have developed a system with direct georeferencing onboard drone to be used combined with hyperspectral frame cameras in real-time remote sensing applications. The objective of this study is to evaluate the real-time georeferencing comparing with post-processing solutions. Experimental data sets were captured in agricultural and forested test sites using the system. The accuracy of onboard georeferencing data were better than 0.5 m. The results showed that the real-time remote sensing is promising and feasible in both test sites. © Authors 2018. CC BY 4.0 License.Peer reviewe

Recording behaviour of indoor-housed farm animals automatically using machine vision technology: a systematic review

Large-scale phenotyping of animal behaviour traits is time consuming and has led to increased demand for technologies that can automate these procedures. Automated tracking of animals has been successful in controlled laboratory settings, but recording from animals in large groups in highly variable farm settings presents challenges. The aim of this review is to provide a systematic overview of the advances that have occurred in automated, high throughput image detection of farm animal behavioural traits with welfare and production implications. Peer-reviewed publications written in English were reviewed systematically following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. After identification, screening, and assessment for eligibility, 108 publications met these specifications and were included for qualitative synthesis. Data collected from the papers included camera specifications, housing conditions, group size, algorithm details, procedures, and results. Most studies utilized standard digital colour video cameras for data collection, with increasing use of 3D cameras in papers published after 2013. Papers including pigs (across production stages) were the most common (n = 63). The most common behaviours recorded included activity level, area occupancy, aggression, gait scores, resource use, and posture. Our review revealed many overlaps in methods applied to analysing behaviour, and most studies started from scratch instead of building upon previous work. Training and validation sample sizes were generally small (mean±s.d. groups = 3.8±5.8) and in data collection and testing took place in relatively controlled environments. To advance our ability to automatically phenotype behaviour, future research should build upon existing knowledge and validate technology under commercial settings and publications should explicitly describe recording conditions in detail to allow studies to be reproduced

Guidance on Health and Safety at Work. Design Safety and Fire-fighting Systems in Urban Rail Transport Networks

In this paper, considering the importance and safety status of urban train systems, we study and assess the urban management requirements and requirements for equipping the inner city network using the results of “cost-benefit” techniques in order to analyze the methods Fire control and fire, as well as the use of fire safety systems in the urban train network. On the other hand, the development of tools for measuring and comparing the effectiveness of fire prevention and fire prevention measures in various rail transportation systems, which are very useful in various safety engineering methods in the design of mass transportation systems such as LRT or tram. And can be effective in analyzing the fire safety of its systems

Auditory Modulation of Multisensory Representations

Motor control and motor learning as well as interpersonal coordination are based on motor perception and emergent perceptuomotor representations. At least in early stages motor learning and interpersonal coordination are emerging heavily on visual information in terms of observing others and transforming the information into internal representations to guide owns behavior. With progressing learning, also other perceptual modalities are added when a new motor pattern is established by repeated physical exercises. In contrast to the vast majority of publications on motor learning and interpersonal coordination referring to a certain perceptual modality here we look at the perceptual system as a unitary system coordinating and unifying the information of all involved perceptual modalities. The relation between perceptual streams of different modalities, the intermodal processing and multisensory integration of information as a basis for motor control and learning will be the main focus of this contribution. Multi-/intermodal processing of perceptual streams results in multimodal representations and opens up new approaches to support motor learning and interpersonal coordination: Creating an additional perceptual stream adequately auditory movement information can be generated suitable to be integrated with information of other modalities and thereby modulating the resulting perceptuomotor representations without the need of attention and higher cognition. Here, the concept of a movement defined real-time acoustics is used to serve the auditory system in terms of an additional movement-auditory stream. Before the computational approach of kinematic real-time sonification is finally described, a special focus is directed to the level of adaptation modules of the internal models. Furthermore, this concept is compared with different approaches of additional acoustic movement information. Moreover, a perspective of this approach is given in a broad spectrum of new applications of supporting motor control and learning in sports and motor rehabilitation as well as a broad spectrum of joint action and interpersonal coordination between humans but also concerning human-robot-interaction. The final publication is available at Springer via https://doi.org/10.1007/978-3-030-01692-0_20.European Commission/H2020- FETPROACT-2014/641321/E