Mobile Glaucoma Detection Application

Glaucoma is a debilitating optical degeneration disease that can lead to vision loss and eventually blindness. Given its asymptomatic nature, most people with Glaucoma aren’t even aware that they have the disease. As a result, the disease is often left untreated until it is too late. Detecting the presence of Glaucoma is one of the most important steps in treating Glaucoma, but is unfortunately also the most difficult to enforce. The Mobile Glaucoma Detection application aims to reduce the growing number of individuals who are unaware that they have Glaucoma by providing a simple detection mechanism to notify users if they are at risk. The system does this by enabling its users to independently conduct Tonometry exams through the application. Tonometry examinations allow doctors to determine if the intra-ocular pressure levels in a person’s eyes put them at risk for Glaucoma. The M.G.D.A(Mobile Glaucoma Detection Application) allows users to determine their intra-ocular pressure levels from the comfort of their own home via a special contact lens paired with a smartphone application. The system also offers users the opportunity to monitor, regulate, and track their use and progress through the system

Brainatwork: Logging Cognitive Engagement and Tasks in the Workplace Using Electroencephalography

Today's workplaces are dynamic and complex. Digital data sources such as email and video conferencing aim to support workers but also add to their burden of multitasking. Psychophysiological sensors such as Electroencephalography (EEG) can provide users with cues about their cognitive state. We introduce BrainAtWork, a workplace engagement and task logger which shows users their cognitive state while working on different tasks. In a lab study with eleven participants working on their own real-world tasks, we gathered 16 hours of EEG and PC logs which were labeled into three classes: central, peripheral and meta work. We evaluated the usability of BrainAtWork via questionnaires and interviews. We investigated the correlations between measured cognitive engagement from EEG and subjective responses from experience sampling probes. Using random forests classification, we show the feasibility of automatically labeling work tasks into work classes. We discuss how BrainAtWork can support workers on the long term through encouraging reflection and helping in task scheduling

Tailored gamification and serious game framework based on fuzzy logic for saving energy in connected thermostats

Connected thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes

Enabling environmental fingerprinting with an NFC-powered sensor board

Abstract. In recent times, people have become concerned about their environmental conditions, amid deteriorating global statistics on bad air quality, global warming and UV light exposure. Conventional technologies for reading environmental conditions are expensive, bulky and situated, yet, people are mobile and need portable tools to be aware of their immediate environmental conditions on demand. Smartphones are now widely used, endowed with sensors and wireless communication technologies such as Bluetooth, and Near Field Communication (NFC) for external sensor connectivity, making smartphones a viable tool for fingerprinting the environment. This thesis outlines the design, evaluation and implementation of a mobile-enabled system for environmental data collection using a portable NFC powered sensor board. The name of the system developed in this thesis is the S3 system. The S3 system is a two-tier system which consists of S3 Android application and an online dashboard with a data repository. The S3 Android application is used for collecting and visualising environmental data; temperature, humidity, UV, ambient light, with a smartphone and a credit card-size NFC powered sensor board. The sensor data is then periodically synced to the online data repository. Additional features of the S3 application include automated feedback sampling, introductory tutorial, and user preference settings. The thesis further details the design and implementation process with scenarios, use cases, paper sketches, expert review of sketches, interface mockups, evaluation of prototype with a user study, quantitative and qualitative analysis of user study data, and finally the implementation of the S3 application. The thesis also presents a test run to demonstrate the capabilities of the S3 system as a mobile-enabled solution for crowdsourced environmental fingerprint datasets. To the end user, the work in this thesis provides the S3 application and the NFC powered sensor card as a portable tool for personalised environmental fingerprinting. On the other hand, the intervention in this thesis will have an impact on research since the crowdsourced environmental fingerprint datasets can be valuable datasets for research. As a TEKES project, the solution also provides a proof of concept for further improvement and deployment into the commercial software market

EXTREMA:a portable assessement of asthma symptoms due to extreme climate change

Abstract. This thesis work focuses on developing an intelligent mobile application that presents and highlights the health effects of climate change on asthma patients. The Android mobile application ‘EXTREMA’ is targeted towards patients in various scenarios, e.g., health, lifestyle, and education. The ‘EXTREMA’ application receives input from a patient along with smart weather sensor and the GPS (Global Positioning System) location sensor in the smartphone and communicates over the Internet with a remote server (Aware) accessible by research professionals who are in charge of the remote monitoring of the patients. This thesis outlines the design, implementation, and evaluation via the deployment of a system aimed to help both individual users and researchers to efficiently gather self-reported symptoms data, and medication record according to weather conditions and user location. For gathering the data, there was no direct interaction with the users (asthma patients). However, during and after the development, the final version of the application was tested and evaluated during the thesis. Different measures were taken regarding the performance of the application, such as data loading, number of users, efficiency and accuracy of the weather sensor data. The major output of the thesis is the application system, which can be used, by users and researchers to record medication and symptoms data in a meaningful format for future use. Hence, the main contribution is also towards improving the health of asthma patients and conducting research in the area

Smartphone as an Edge for Context-Aware Real-Time Processing for Personal e-Health

The medical domain is facing an ongoing challenge of how patients can share their health information and timeline with healthcare providers. This involves secure sharing, diverse data types, and formats reported by healthcare-related devices. A multilayer framework can address these challenges in the context of the Internet of Medical Things (IoMT). This framework utilizes smartphone sensors, external services, and medical devices that measure vital signs and communicate such real-time data with smartphones. The smartphone serves as an “edge device” to visualize, analyze, store, and report context- aware data to the cloud layer. Focusing on medical device connectivity, mobile security, data collection, and interoperability for frictionless data processing allows for building context-aware personal medical records (PMRs). These PMRs are then securely transmitted through a communication protocol, Message Queuing Telemetry Transport (MQTT), to be then utilized by authorized medical staff and healthcare institutions. MQTT is a lightweight, intuitive, and easy-to-use messaging protocol suitable for IoMT systems. Consequently, these PMRs are to be further processed in a cloud computing platform, Amazon Web Services (AWS). Through AWS and its services, architecting a customized data pipeline from the mobile user to the cloud allows displaying of useful analytics to healthcare stakeholders, secure storage, and SMS notifications. Our results demonstrate that this framework preserves the patient’s health-related timeline and shares this information with professionals. Through a serverless Business intelligence interactive dashboard generated from AWS QuickSight, further querying and data filtering techniques are applied to the PMRs which identify key metrics and trends

Synergy: An Energy Monitoring and Visualization System

The key to becoming a more sustainable society is first learning to take responsibility for the role we play in energy consumption. Real-time energy usage gives energy consumers a sense of responsibility over what they can do to accomplish a much larger goal for the planet, and practically speaking, what they can do to lower the cost to their wallets. Synergy is an energy monitoring and visualization system that enables users to gather information about the energy consumption in a building – small or large – and display that data for the user in real-time. The gathered energy usage data is processed on the edge before being stored in the cloud. The two main benefits of edge processing are issuing electricity hazard warnings immediately and preserving user privacy. In addition to being a scalable solution that intended for use in individual households, commercial offices and city power grids, Synergy is open-source so that it can be implemented more widely. This paper contains a system overview as well as initial finding based on the data collected by Synergy before assessing the impact the system can have on society

Microservices suite for smart city applications

Smart Cities are approaching the Internet of Things (IoT) World. Most of the first-generation Smart City solutions are based on Extract Transform Load (ETL); processes and languages that mainly support pull protocols for data gathering. IoT solutions are moving forward to event-driven processes using push protocols. Thus, the concept of IoT applications has turned out to be widespread; but it was initially “implemented” with ETL; rule-based solutions; and finally; with true data flows. In this paper, these aspects are reviewed, highlighting the requirements for smart city IoT applications and in particular, the ones that implement a set of specific MicroServices for IoT Applications in Smart City contexts. Moreover; our experience has allowed us to implement a suite of MicroServices for Node-RED; which has allowed for the creation of a wide range of new IoT applications for smart cities that includes dashboards, IoT Devices, data analytics, discovery, etc., as well as a corresponding Life Cycle. The proposed solution has been validated against a large number of IoT applications, as it can be verified by accessing the https://www.Snap4City.org portal; while only three of them have been described in the paper. In addition, the reported solution assessment has been carried out by a number of smart city experts. The work has been developed in the framework of the Select4Cities PCP (PreCommercial Procurement), funded by the European Commission as Snap4City platform

Cloud Computing Strategies for Enhancing Smart Grid Performance in Developing Countries

In developing countries, the awareness and development of Smart Grids are in the introductory stage and the full realisation needs more time and effort. Besides, the partially introduced Smart Grids are inefficient, unreliable, and environmentally unfriendly. As the global economy crucially depends on energy sustainability, there is a requirement to revamp the existing energy systems. Hence, this research work aims at cost-effective optimisation and communication strategies for enhancing Smart Grid performance on Cloud platforms