ITERL: A Wireless Adaptive System for Efficient Road Lighting

This work presents the development and construction of an adaptive street lighting system that improves safety at intersections, which is the result of applying low-power Internet of Things (IoT) techniques to intelligent transportation systems. A set of wireless sensor nodes using the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard with additional internet protocol (IP) connectivity measures both ambient conditions and vehicle transit. These measurements are sent to a coordinator node that collects and passes them to a local controller, which then makes decisions leading to the streetlight being turned on and its illumination level controlled. Streetlights are autonomous, powered by photovoltaic energy, and wirelessly connected, achieving a high degree of energy efficiency. Relevant data are also sent to the highway conservation center, allowing it to maintain up-to-date information for the system, enabling preventive maintenance.Consejería de Fomento y Vivienda Junta de Andalucía G-GI3002 / IDIOFondo Europeo de Desarrollo Regional G-GI3002 / IDI

Enhancing web supported learning in higher education by adding a management layer to LMSs

There are many situations in the e-Learning experiences that can compromise the success of the courses. Many times simple reasons are great enough to motivate people to abandon them. For example, if someone does not execute a programmed activity inside the defined window of time, it can compromise the rest of the course to that person. In such situations it would be important that the teacher knew about the situation in useful time, to be able to take any corrective action. Another example could be presented, involving the professor and the learners. Let us assume that an activity A2 is programmed to be executed by the learners and that it depends on the previous knowledge of the result of the evaluation of a work submitted by the learners to the teacher (activity A1). If the teacher doesn’t inform the learners about their classification in useful time, that can compromise the execution of the activity A2. It seems to be necessary to use mechanisms of automatic management, in real time, of the envolvement of each participant in a distance learning course using LMS (Learning Management System). Such a functionality allows the detection of deviations to the scheduled activities planned for each actor. If it is the case, the referred mechanism can initiate the process of sending notifications to the relevant entities, enabling the correction of these deviations. Several organizations and consortiuns, involving the industry, governmental institutions and universities, are developing projects of standardization. It seemed important to us to see how the referred aspects were covered by those projects, and to perceive how it could be possible to articulate our work with the ones that are available from these organizations and consortiuns. This article describes the work that the authors are developing towards the specification of a layer for real-time management of user interactions with LMSs, during the operationalization of a course, and also includes a management meta-data model, related to that management layer

An intelligent information forwarder for healthcare big data systems with distributed wearable sensors

© 2016 IEEE. An increasing number of the elderly population wish to live an independent lifestyle, rather than rely on intrusive care programmes. A big data solution is presented using wearable sensors capable of carrying out continuous monitoring of the elderly, alerting the relevant caregivers when necessary and forwarding pertinent information to a big data system for analysis. A challenge for such a solution is the development of context-awareness through the multidimensional, dynamic and nonlinear sensor readings that have a weak correlation with observable human behaviours and health conditions. To address this challenge, a wearable sensor system with an intelligent data forwarder is discussed in this paper. The forwarder adopts a Hidden Markov Model for human behaviour recognition. Locality sensitive hashing is proposed as an efficient mechanism to learn sensor patterns. A prototype solution is implemented to monitor health conditions of dispersed users. It is shown that the intelligent forwarders can provide the remote sensors with context-awareness. They transmit only important information to the big data server for analytics when certain behaviours happen and avoid overwhelming communication and data storage. The system functions unobtrusively, whilst giving the users peace of mind in the knowledge that their safety is being monitored and analysed

Modelling a layer for real-time management of interactions in web based distance learning

In the last few years, the University of Aveiro, Portugal, has been offering several distance learning courses over the Web, using e-learning platforms. Experience showed that different editions of a same course, using the same contents and structure, and having similar target learners, had different success rates. What would be the reason for that? A hypothesis was considered: The level of success could be directly related with the remote follow-up of the learners’ participation in the courses; the best results usually occur when the follow-up is closer. The existing e-learning platforms offer and the standardization works being developed by organizations and consortiums like IMS (IMS Global Learning Consortium, Inc), ADL SCORM (Advanced Distributed Learning Sherable Content Object Reference Model), IEEE LTSC LOM (Institute of Electrical and Electronic Engineers Learning Technologies Standard Committee Learning Object Metadata), ARIADNE (ARIADNE Foundation for the European Knowledge Pool), AICC CMI (Aviation Industry CBT Committee Computer Managed Instruction), etc, don’t cover the course monitorization concerns mentioned. Those projects were focused on aspects like contents and its delivery in the context of the execution of the courses’ activities. This is even true in the SCORM project that doesn’t include any reference to the management of the e-learning processes. Recently, in the context of the IMS Global Consortium, a new project designated IMS LD (Learning Design) is under development, providing a framework for the description of learning units under a three level model. In the most recently defined level, the C level, some functionalities related to notifications were proposed, expressing similar concerns to the ones that triggered our research. However, the extent at which IMS LD takes the functionalities is, from our point of view, not complete. This article describes a proposal of a reference model and functionalities towards a specification of a layer for real-time management of user interactions on LMSs, and its possible integration with the ADL SCORM standard proposal. The paper includes a discussion of the management metadata model for the LMS sub-system and how the integration of the management module under SCORM may be achieved

Pump and Dumps in the Bitcoin Era: Real Time Detection of Cryptocurrency Market Manipulations

In the last years, cryptocurrencies are increasingly popular. Even people who are not experts have started to invest in these securities and nowadays cryptocurrency exchanges process transactions for over 100 billion US dollars per month. However, many cryptocurrencies have low liquidity and therefore they are highly prone to market manipulation schemes. In this paper, we perform an in-depth analysis of pump and dump schemes organized by communities over the Internet. We observe how these communities are organized and how they carry out the fraud. Then, we report on two case studies related to pump and dump groups. Lastly, we introduce an approach to detect the fraud in real time that outperforms the current state of the art, so to help investors stay out of the market when a pump and dump scheme is in action.Comment: Accepted for publication at The 29th International Conference on Computer Communications and Networks (ICCCN 2020

The Double-edged Sword: A Mixed Methods Study of the Interplay between Bipolar Disorder and Technology Use

Human behavior is increasingly reflected or acted out through technology. This is of particular salience when it comes to changes in behavior associated with serious mental illnesses including schizophrenia and bipolar disorder. Early detection is crucial for these conditions but presently very challenging to achieve. Potentially, characteristics of these conditions\u27 traits and symptoms, at both idiosyncratic and collective levels, may be detectable through technology use patterns. In bipolar disorder specifically, initial evidence associates changes in mood with changes in technology-mediated communication patterns. However much less is known about how people with bipolar disorder use technology more generally in their lives, how they view their technology use in relation to their illness, and, perhaps most crucially, the causal relationship (if any exists) between their technology use and their disease. To address these uncertainties, we conducted a survey of people with bipolar disorder (N = 84). Our results indicate that technology use varies markedly with changes in mood and that technology use broadly may have potential as an early warning signal of mood episodes. We also find that technology for many of these participants is a double-edged sword: acting as both a culprit that can trigger or exacerbate symptoms as well as a support mechanism for recovery. These findings have implications for the design of both early warning systems and technology-mediated interventions

Advanced observation and telemetry heart system utilizing wearable ECG device and a Cloud platform

Short lived chest pain episodes of post PCI patients represent the most common clinical scenario treated in the Accidents and Emergency Room. Continuous ECG monitoring could substantially diminish such hospital admissions and related ambulance calls. Delivering community based, easy-To-handle, easy to wear, real time electrocardiography systems is still a quest, despite the existence of electronic electrocardiography systems for several decades. The PATRIOT system serves this challenge via a 12-channel, easy to wear, easy to carry, mobile linked, miniaturized automatic ECG device and a Cloud platform. The system may deliver high quality electrocardiograms of a patient to medical personnel either on the spot or remotely both in a synchronous or asynchronous mode, enhancing autonomy, mobility, quality of life and safety of recently treated coronary artery disease patients