Monitoring wild animal communities with arrays of motion sensitive camera traps

Studying animal movement and distribution is of critical importance to addressing environmental challenges including invasive species, infectious diseases, climate and land-use change. Motion sensitive camera traps offer a visual sensor to record the presence of a broad range of species providing location -specific information on movement and behavior. Modern digital camera traps that record video present new analytical opportunities, but also new data management challenges. This paper describes our experience with a terrestrial animal monitoring system at Barro Colorado Island, Panama. Our camera network captured the spatio-temporal dynamics of terrestrial bird and mammal activity at the site - data relevant to immediate science questions, and long-term conservation issues. We believe that the experience gained and lessons learned during our year long deployment and testing of the camera traps as well as the developed solutions are applicable to broader sensor network applications and are valuable for the advancement of the sensor network research. We suggest that the continued development of these hardware, software, and analytical tools, in concert, offer an exciting sensor-network solution to monitoring of animal populations which could realistically scale over larger areas and time spans

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Recognition of elementary arm movements using orientation of a tri-axial accelerometer located near the wrist

In this paper we present a method for recognising three fundamental movements of the human arm (reach and retrieve, lift cup to mouth, rotation of the arm) by determining the orientation of a tri-axial accelerometer located near the wrist. Our objective is to detect the occurrence of such movements performed with the impaired arm of a stroke patient during normal daily activities as a means to assess their rehabilitation. The method relies on accurately mapping transitions of predefined, standard orientations of the accelerometer to corresponding elementary arm movements. To evaluate the technique, kinematic data was collected from four healthy subjects and four stroke patients as they performed a number of activities involved in a representative activity of daily living, 'making-a-cup-of-tea'. Our experimental results show that the proposed method can independently recognise all three of the elementary upper limb movements investigated with accuracies in the range 91–99% for healthy subjects and 70–85% for stroke patients

Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People

This paper aims to contribute to the field of ambient intelligence from the perspective of real environments, where noise levels in datasets are significant, by showing how machine learning techniques can contribute to the knowledge creation, by promoting software sensors. The created knowledge can be actionable to develop features helping to deal with problems related to minimally labelled datasets. A case study is presented and analysed, looking to infer high-level rules, which can help to anticipate abnormal activities, and potential benefits of the integration of these technologies are discussed in this context. The contribution also aims to analyse the usage of the models for the transfer of knowledge when different sensors with different settings contribute to the noise levels. Finally, based on the authors’ experience, a framework proposal for creating valuable and aggregated knowledge is depicted.This research was partially funded by Fundación Tecnalia Research & Innovation, and J.O.-M. also wants to recognise the support obtained from the EU RFCS program through project number 793505 ‘4.0 Lean system integrating workers and processes (WISEST)’ and from the grant PRX18/00036 given by the Spanish Secretaría de Estado de Universidades, Investigación, Desarrollo e Innovación del Ministerio de Ciencia, Innovación y Universidades

Root Zone Sensors for Irrigation Management in Intensive Agriculture

Crop irrigation uses more than 70% of the world’s water, and thus, improving irrigation efficiency is decisive to sustain the food demand from a fast-growing world population. This objective may be accomplished by cultivating more water-efficient crop species and/or through the application of efficient irrigation systems, which includes the implementation of a suitable method for precise scheduling. At the farm level, irrigation is generally scheduled based on the grower’s experience or on the determination of soil water balance (weather-based method). An alternative approach entails the measurement of soil water status. Expensive and sophisticated root zone sensors (RZS), such as neutron probes, are available for the use of soil and plant scientists, while cheap and practical devices are needed for irrigation management in commercial crops. The paper illustrates the main features of RZS’ (for both soil moisture and salinity) marketed for the irrigation industry and discusses how such sensors may be integrated in a wireless network for computer-controlled irrigation and used for innovative irrigation strategies, such as deficit or dual-water irrigation. The paper also consider the main results of recent or current research works conducted by the authors in Tuscany (Italy) on the irrigation management of container-grown ornamental plants, which is an important agricultural sector in Italy

A novel wireless low-cost inclinometer made from combining the measurements of multiple MEMS gyroscopes and accelerometers

Structural damage detection using inclinometers is getting wide attention from researchers. However, the high price of inclinometers limits this system to unique structures with a relatively high structural health monitoring (SHM) budget. This paper presents a novel low-cost inclinometer, the low-cost adaptable reliable angle-meter (LARA), which combines five gyroscopes and five accelerometers to measure inclination. LARA incorporates Internet of Things (IoT)-based microcontroller technology enabling wireless data streaming and free commercial software for data acquisition. This paper investigates the accuracy, resolution, Allan variance and standard deviation of LARA produced with a different number of combined circuits, including an accelerometer and a gyroscope. To validate the accuracy and resolution of the developed device, its results are compared with those obtained by numerical slope calculations and a commercial inclinometer (HI-INC) in laboratory conditions. The results of a load test experiment on a simple beam model show the high accuracy of LARA (0.003 degrees). The affordability and high accuracy of LARA make it applicable for structural damage detection on bridges using inclinometers.The authors are indebted to the Spanish Ministry of Economy and Competitiveness for the funding provided through the research project BIA2017-86811-C2-1-R directed by José Turmo and BIA2017-86811-C2-2-R. All these projects are funded with FEDER funds. The authors are also indebted to the Secretaria d’ Universitats i Recerca de la Generalitat de Catalunya, Catalunya, Spain for the funding provided through Agaur (2017 SGR 1482). It is also to be noted that funding for this research has been provided for Seyedmilad Komarizadehasl by Spanish Agencia Estatal de Investigación del Ministerio de Ciencia Innovación y Universidades grant and the Fondo Social Europeo grant (PRE2018-083238).Peer ReviewedPostprint (published version

Towards safer mining: the role of modelling software to find missing persons after a mine collapse

Purpose. The purpose of the study is to apply science and technology to determine the most likely location of a container in which three miners were trapped after the Lily mine disaster. Following the collapse of the Crown Pillar at Lily Mine in South Africa on the 5th of February 2016, there was a national outcry to find the three miners who were trapped in a surface container lamp room that disappeared in the sinkhole that formed during the surface col-lapse. Methods. At a visit to Lily Mine on the 9th of March, the Witwatersrand Mining Institute suggested a two-way strategy going forward to find the container in which the miners are trapped and buried. The first approach, which is the subject of this paper, is to test temporal 3D modeling software technology to locate the container, and second, to use scientific measurement and testing technologies. The overall methodology used was to first, request academia and research entities within the University to supply the WMI with ideas, which ideas list was compiled as responses came in. These were scrutinized and literature gathered for a conceptual study on which these ideas are likely to work. The software screening and preliminary testing of such software are discussed in this article. Findings. The findings are that software modeling is likely to locate the present position of the container, but accurate data and a combination of different advanced software packages will be required, but at tremendous cost. Originality. This paper presents original work on how software technology can be used to locate missing miners. Practical implications. The two approaches were not likely to recover the miners alive because of the considerable time interval, but will alert the rescue team and mine workers when they come in close proximity to them.Мета. Визначення можливого місця локалізації лампового приміщення контейнера, в якому опинилися три шахтаря після аварії на шахті Лілі (Барбертон, Мпумаланга) методом комп’ютерного моделювання. Після обвалення стельового цілика на шахті Лілі 5 лютого 2016 року почалася національна кампанія з порятунку трьох шахтарів, які залишилися у ламповому приміщенні поверхневого транспортного контейнера, що провалився в утворену після вибуху воронку. Методика. Співробітниками Гірничого Інституту (Уітуотерс) запропонована двостадійна стратегія пошуку контейнера, в якому існує ймовірність знаходження шахтарів. В рамках першого підходу (який розглядається у даній статті) для виявлення контейнера здійснювалось випробування комп’ютерної технології 3D-моделювання в часі. Другий підхід передбачав технологію проведення наукового вимірювання та експерименту. В цілому, методологія включала, насамперед, підключення викладацького та наукового складу університету до вирішення проблеми шляхом комплексної генерації ідей, які були об’єднані в загальний список, вивчені із залученням відповідних літературних джерел, і найбільш реалістичні ідеї були виділені із загального переліку. Дана стаття розглядає результати комп’ютерної експертизи цих ідей та перевірки надійності відповідного програмного забезпечення. Результати. Для зручності моделювання процес обвалення був розділений на три окремі фази: руйнування воронки, руйнування західного схилу та небезпека ковзання на південних схилах. Ідентифіковано програмні технології, які можуть імітувати рух контейнера у перших двох фазах обвалення. В результаті моделювання у програмному забезпеченні ParaView виявлено місце розташування даного контейнера. Виконано аналіз південного схилу за допомогою ArcGIS і складені карти небезпеки схилу для району, а також підземні карти порятунку з маршрутами евакуації. Встановлено, що комп’ютерне моделювання може визначити місцезнаходження контейнера, але для цього потрібні точні вихідні дані й комплекс дорогих високоефективних програмних пакетів. Наукова новизна. Вперше застосовано комплекс комп’ютерних технологій та програмного забезпечення для пошуку зниклих шахтарів після аварійних ситуацій у підземному просторі шахт. Практична значимість. При застосуванні двостадійної стратегії пошуку шахтарів, що опинилися під завалом порід, команда рятувальників отримає сигнал про наближення до їх місцезнаходження.Цель. Определение возможного места локализации лампового помещения контейнера, в котором оказались три шахтера после аварии на шахте Лили (Барбертон, Мпумаланга) методом компьютерного моделирования. После обрушения потолочного целика на шахте Лили 5 февраля 2016 года началась национальная кампания по спасению трех шахтеров, оставшихся в ламповом помещении поверхностного транспортного контейнера, который провалился в воронку, образовавшуюся после взрыва. Методика. Сотрудниками Горного Института (Уитуотерс) предложена двухстадийная стратегия поиска контейнера, в котором существует вероятность нахождения шахтеров. В рамках первого подхода (который рассматривается в данной статье) для обнаружения контейнера производилось испытание компьютерной технологии 3D-моделирования во времени. Второй подход предполагал технологию проведения научного измерения и эксперимента. В целом, методология включала, прежде всего, подключение преподавательского и научного состава университета к решению проблемы путем комплексной генерации идей, которые были объединены в общий список, изучены с привлечением соответствующих литературных источников, и наиболее реалистичные идеи были выделены из общего списка. Настоящая статья рассматривает результаты компьютерной экспертизы данных идей и проверки надежности соответствующего программного обеспечения. Результаты. Для удобства моделирования процесс обрушения был разделен на три отдельные фазы: разрушение воронки, разрушение западного склона и опасность скольжения на южных склонах. Идентифицированы программные технологии, которые могут имитировать движение контейнера в первых двух фазах обрушения. В результате моделирования в программном обеспечении ParaView выявлено местоположение данного контейнера. Выполнен анализа южного склона с помощью ArcGIS и составлены карты опасности склона для района, а также подземные карты спасения с маршрутами эвакуации. Установлено, что компьютерное моделирование может определить местонахождение контейнера, но для этого нужны точные исходные данные и комплекс дорогостоящих высокоэффективных программных пакетов. Научная новизна. Впервые применен комплекс компьютерных технологий и программного обеспечения для поиска пропавших шахтеров после аварийных ситуаций в подземном пространстве шахт. Практическая значимость. При применении двухстадийной стратегии поиска шахтеров, оказавшихся под завалом пород, команда горноспасателей получит сигнал о приближении к их местонахождению.The results of the article were obtained without the support of any of the projects or funding

Environmental monitoring: landslide assessment and risk management (Test site: Vernazza, Cinque Terre Natural Park)

Natural disasters, whether of meteorological origin such as cyclones, floods, tornadoes and droughts or having geological nature such as earthquakes, volcanoes and landslide, are well known for their devastating impacts on human life, economy and environment. Over recent decades, the people and the societies are becoming more vulnerable; although the frequency of natural events may be constant, human activities contribute to their increased intensity. Indeed, every year millions of people are affected by natural disasters globally and, only in the last decade, more than 80% of all disaster-related deaths were caused by natural hazards. The PhD work is part of the activities for the support and development of methodologies useful to improve the management of environmental emergencies. In particular, it focused on the analysis of environmental monitoring and disaster risk management, a systematic approach to identify, to assess and to reduce the potential risks produced by a disaster. This method (Disaster Risk Management) aims to reduce socio-economic vulnerabilities and deals with natural and man-made events. In the PhD thesis, in particular, the slope movements have been evaluated. Slope failures are generally not so costly as earthquakes or major floods, but they are more widespread, and over the years may cause more property loss than any other geological hazard. In many developing regions slope failures constitute a continuing and serious impact on the social and economic structure. Specifically, the Italian territory has always been subject to instability phenomena, because of the geological and morphological characteristic and because of "extreme" weather events that are repeated more frequently than in the past, in relation to climate change. Currently these disasters lead to the largest number of victims and damages to settlements, infrastructure and historical and cultural environmental, after the earthquakes. The urban development, especially in recent decades, resulted in an increase of the assets at risk and unstable areas, often due to constant human intervention badly designed that led to instability also places previously considered "safe". Prevention is therefore essential to minimize the damages caused by landslides The objectives of the conducted research were to investigate the different techniques and to check their potentiality, in order to evaluate the most appropriate instrument for landslide hazard assessment in terms of better compromise between time to perform the analysis and expected results. The attempt is to evaluate which are the best methodologies to use according to the scenario, taking into consideration both reachable accuracies and time constraints. Careful considerations will be performed on strengths, weaknesses and limitations inherent to each methodology. The characteristics associated with geographic, or geospatial, information technologies facilitate the integration of scientific, social and economic data, opening up interesting possibilities for monitoring, assessment and change detection activities, thus enabling better informed interventions in human and natural systems. This is an important factor for the success of emergency operations and for developing valuable natural disaster preparedness, mitigation and prevention systems. The test site was the municipality of Vernazza, which in October 2011 was subject to a extreme rainfall which led to the occurrence of a series of landslides along the Vernazzola stream, which have emphasized the flood event that affected the water cours

Detecting Irregular Patterns in IoT Streaming Data for Fall Detection

Detecting patterns in real time streaming data has been an interesting and challenging data analytics problem. With the proliferation of a variety of sensor devices, real-time analytics of data from the Internet of Things (IoT) to learn regular and irregular patterns has become an important machine learning problem to enable predictive analytics for automated notification and decision support. In this work, we address the problem of learning an irregular human activity pattern, fall, from streaming IoT data from wearable sensors. We present a deep neural network model for detecting fall based on accelerometer data giving 98.75 percent accuracy using an online physical activity monitoring dataset called "MobiAct", which was published by Vavoulas et al. The initial model was developed using IBM Watson studio and then later transferred and deployed on IBM Cloud with the streaming analytics service supported by IBM Streams for monitoring real-time IoT data. We also present the systems architecture of the real-time fall detection framework that we intend to use with mbientlabs wearable health monitoring sensors for real time patient monitoring at retirement homes or rehabilitation clinics.Comment: 7 page