A Review of Multisensor Data Fusion Solutions in Smart Manufacturing: Systems and Trends.

Manufacturing companies increasingly become "smarter" as a result of the Industry 4.0 revolution. Multiple sensors are used for industrial monitoring of machines and workers in order to detect events and consequently improve the manufacturing processes, lower the respective costs, and increase safety. Multisensor systems produce big amounts of heterogeneous data. Data fusion techniques address the issue of multimodality by combining data from different sources and improving the results of monitoring systems. The current paper presents a detailed review of state-of-the-art data fusion solutions, on data storage and indexing from various types of sensors, feature engineering, and multimodal data integration. The review aims to serve as a guide for the early stages of an analytic pipeline of manufacturing prognosis. The reviewed literature showed that in fusion and in preprocessing, the methods chosen to be applied in this sector are beyond the state-of-the-art. Existing weaknesses and gaps that lead to future research goals were also identified.

A social media analytics platform visualising the spread of COVID-19 in Italy via exploitation of automatically geotagged tweets.

Social media play an important role in the daily life of people around the globe and users have emerged as an active part of news distribution as well as production. The threatening pandemic of COVID-19 has been the lead subject in online discussions and posts, resulting to large amounts of related social media data, which can be utilised to reinforce the crisis management in several ways. Towards this direction, we propose a novel framework to collect, analyse, and visualise Twitter posts, which has been tailored to specifically monitor the virus spread in severely affected Italy. We present and evaluate a deep learning localisation technique that geotags posts based on the locations mentioned in their text, a face detection algorithm to estimate the number of people appearing in posted images, and a community detection approach to identify communities of Twitter users. Moreover, we propose further analysis of the collected posts to predict their reliability and to detect trending topics and events. Finally, we demonstrate an online platform that comprises an interactive map to display and filter analysed posts, utilising the outcome of the localisation technique, and a visual analytics dashboard that visualises the results of the topic, community, and event detection methodologies.

Making urban water smart: the SMART-WATER solution.

The rise of Internet of Things (IoT), coupled with the advances in Artificial Intelligence technologies and cloud-based applications, have caused fundamental changes in the way societies behave. Enhanced connectivity and interactions between physical and cyber worlds create 'smart' solutions and applications to serve society's needs. Water is a vital resource and its management is a critical issue. ICT achievements gradually deployed within the water industry provide an alternative, smart and novel way to improve water management efficiently. Contributing to this direction, we propose a unified framework for urban water management, exploiting state-of-the-art IoT solutions for remote telemetry and control of water consumption in combination with machine learning-based processes. The SMART-WATER platform aims to foster water utility companies by enhancing water management and decision-making processes, providing innovative solutions to consumers for smart water utilisation.

A French-Greek Cross-Site Comparison Study of the Use of Automatic Video Analyses for the Assessment of Autonomy in Dementia Patients.

BACKGROUND: At present, the assessment of autonomy in daily living activities, one of the key symptoms in Alzheimer's disease (AD), involves clinical rating scales. METHODS: In total, 109 participants were included. In particular, 11 participants during a pre-test in Nice, France, and 98 participants (27 AD, 38 mild cognitive impairment-MCI-and 33 healthy controls-HC) in Thessaloniki, Greece, carried out a standardized scenario consisting of several instrumental activities of daily living (IADLs), such as making a phone call or preparing a pillbox while being recorded. Data were processed by a platform of video signal analysis in order to extract kinematic parameters, detecting activities undertaken by the participant. RESULTS: The video analysis data can be used to assess IADL task quality and provide clinicians with objective measurements of the patients' performance. Furthermore, it reveals that the HC statistically significantly outperformed the MCI, which had better performance compared to the AD participants. CONCLUSIONS: Accurate activity recognition data for the analyses of the performance on IADL activities were obtained.

A Comparative Single-Blind Randomized Controlled Trial With Language Training in People With Mild Cognitive Impairment.

BACKGROUND: Although cognitive training is effective for people with mild cognitive impairment (MCI), it is not clear which format is more effective. OBJECTIVE: To compare the effectiveness of the same language programs when carried out via computer, paper/pencil and orally in people with MCI. METHODS: Seventy-one participants with MCI were randomly classified in 3 experimental and 2 control groups. The experimental groups attended 48 sessions of language training for 6 months. The control groups attended either unstructured sessions or they were on waiting list. RESULTS: Mixed measures analysis of variance, at the follow-up, showed a significant cognitive abilities improvement among the experimental versus control groups. At the end of the language training, the 3 groups presented improvement in cognitive abilities and daily function, while the control groups remained at the same performance level. CONCLUSION: All 3 cognitive language training methods were equally significantly effective.

International Ballroom Dancing Against Neurodegeneration: A Randomized Controlled Trial in Greek Community-Dwelling Elders With Mild Cognitive impairment.

BACKGROUND: Many studies have highlighted the positive effects of dance in people with neurodegenerative diseases. OBJECTIVES: To explore the effects of International Ballroom Dancing on cognitive function in elders with amnestic mild cognitive impairment (aMCI). METHODS: One-hundred twenty-nine elderly patients with aMCI diagnosis (mean age 66.8 ± 10.1 years) were randomly assigned into 2 groups: intervention group (IG, n = 66) and control group (CG, n = 63). The IG exercised systematically for 10 months, and both groups were submitted to extensive neuropsychological assessment prior and after the 10-month period. RESULTS: According to the independent sample t test at the follow-up, significant differences between groups were found in benefit of the IG while the CG showed worse performance in the majority of neuropsychological tests. According to the Student t test, better performance is detected in IG in contrast with CG, which had worse performance almost in all scales. CONCLUSION: Dance may be an important nonpharmacological approach that can benefit cognitive functions.

A Novel and Intelligent Home Monitoring System for Care Support of Elders with Cognitive Impairment.

BACKGROUND: Assistive technology, in the form of a smart home environment, is employed to support people with dementia. OBJECTIVES: To propose a system for continuous and objective remote monitoring of problematic daily living activity areas and design personalized interventions based on system feedback and clinical observations for improving cognitive function and health-related quality of life. METHODS: The assistive technology of the proposed system, including wearable, sleep, object motion, presence, and utility usage sensors, was methodically deployed at four different home installations of people with cognitive impairment. Detection of sleep patterns, physical activity, and activities of daily living, based on the collected sensor data and analytics, was available at all times through comprehensive data visualization solutions. Combined with clinical observation, targeted psychosocial interventions were introduced to enhance the participants' quality of life and improve their cognitive functions and daily functionality. Meanwhile, participants and their caregivers were able to visualize a reduced set of information tailored to their needs. RESULTS: Overall, paired-sample t-test analysis of monitored qualities revealed improvement for all participants in neuropsychological assessment. Moreover, improvement was detected from the beginning to the end of the trial, in physical condition and in the domains of sleep. Detecting abnormalities via the system, for example in sleep quality, such as REM sleep, has proved to be critical to assess current status, drive interventions, and evaluate improvements in a reliable manner. CONCLUSION: It has been proved that the proposed system is suitable to support clinicians to reliably drive and evaluate clinical interventions toward quality of life improvement of people with cognitive impairment.

Our experience with informative and communication technologies (ICT) in dementia.

Our research is implementing high quality next generation services for the Prediction, Early Diagnosis, Monitoring, and Support of patients with Cognitive Impairment (Subjective Cognitive Impairment -SCI-, Mild Cognitive Impairment -MCI-, Mild Dementia) and Education and Training for all stakeholders. Prediction, Early Diagnosis and Monitoring: The first idea was to Research and Develop a novel System using motion detection devices, depth cameras, and intelligent objects of everyday use (ranging from cooking implements such as kitchen to furniture (e.g. sofa, bed, etc.) which are appropriately adapted in order to capture changes of subject's Activities of Daily Living -ADL- and behavioural patterns (including mobility, nutrition, exercising and medication schedule). We also demonstrated the potential of a virtual supermarket (VSM) cognitive training game as a screening tool for patients with MCI in a sample of older adults. We have indicated that this VSM application displayed a correct classification rate (CCR) of 87.30%, achieving a level of diagnostic accuracy similar to standardized neuropsychological tests, which are the gold standard for MCI screening http://www.en-noisis.gr/ Support of patients: Cognitive tasks and cognitive exercises for patients suffering from Alzheimer's Disease (AD) through web-based applications. These exercises have been developed in such a way in order to exploit rich interactive multimedia interfaces (including music) based on human computer interaction principles. To this direction we are implementing a web based portal with supportive services such as (a) on-line monitoring of patient's progress by health care professionals, (b) statistical representation of patients' progress. Multimedia enriched cognitive exercises in virtual reality form (i.e. 3D Serious Games) use suitable modalities for such activities through the creation probable of new brain cells and by assisting the brain to find out alternative methods to execute functions, which are controlled by damaged brain regions. Another program the "robot-programming-as-cognitive-training" approach aims to explore the impact that the activity of programming a friendly robot might have on AD and MCI patients' condition. http://aspad.csd.auth.gr. Another study aimed at investigating the benefits of combined physical and cognitive training on global cognition while assessing the effect of training dosage and exploring the role of several potential effect modifiers. The results indicate that combined physical and cognitive training improves global cognition in a dose-responsive manner but these benefits may be less pronounced in older adults with mild dementia. The long-lasting impact of combined training on the incidence and trajectory of cognitive disorders in relation to its severity should be assessed in future long-term trials. www.longlastingmemories.eu. Finally, Symbiosis is a revolutionary system aiming at providing integrated solutions to a series of problems related with MCI and AD. It is the first integrated AD support system that takes into account patient's response in an adaptive way that fulfills each patient's special needs and provides to caregivers and doctors considerable facilitations, unlocking the potential of innovative supporting role. www.youtube.com/watch?v=BDkLz-T-jYE. Education and training for all stakeholders (i.e. health professionals and informal and formal caregivers) through distance education platforms and e-collaboration services. To augment this effort, the research team integrates biofeedback modules for stress measurement in teleconferences in order to support the emotional awareness of the participants. The depression, anxiety and burden of caregivers were reduced significantly in the same way as in a face to face intervention. http://aspad.csd.auth.gr. In conclusion ICT can help health professionals and caregivers to support in a better way the patients with cognitive, functional and behavioral problems.