Smart Notification Research Articles

Optimized continuous homecare provisioning through distributed data-driven semantic services and cross-organizational workflows

BackgroundIn healthcare, an increasing collaboration can be noticed between different caregivers, especially considering the shift to homecare. To provide optimal patient care, efficient coordination of data and workflows between these different stakeholders is required. To achieve this, data should be exposed in a machine-interpretable, reusable manner. In addition, there is a need for smart, dynamic, personalized and performant services provided on top of this data. Flexible workflows should be defined that realize their desired functionality, adhere to use case specific quality constraints and improve coordination across stakeholders. User interfaces should allow configuring all of this in an easy, user-friendly way.MethodsA distributed, generic, cascading reasoning reference architecture can solve the presented challenges. It can be instantiated with existing tools built upon Semantic Web technologies that provide data-driven semantic services and constructing cross-organizational workflows. These tools include RMLStreamer to generate Linked Data, DIVIDE to adaptively manage contextually relevant local queries, Streaming MASSIF to deploy reusable services, AMADEUS to compose semantic workflows, and RMLEditor and Matey to configure rules to generate Linked Data.ResultsA use case demonstrator is built on a scenario that focuses on personalized smart monitoring and cross-organizational treatment planning. The performance and usability of the demonstrator’s implementation is evaluated. The former shows that the monitoring pipeline efficiently processes a stream of 14 observations per second: RMLStreamer maps JSON observations to RDF in 13.5 ms, a C-SPARQL query to generate fever alarms is executed on a window of 5 s in 26.4 ms, and Streaming MASSIF generates a smart notification for fever alarms based on severity and urgency in 1539.5 ms. DIVIDE derives the C-SPARQL queries in 7249.5 ms, while AMADEUS constructs a colon cancer treatment plan and performs conflict detection with it in 190.8 ms and 1335.7 ms, respectively.ConclusionsExisting tools built upon Semantic Web technologies can be leveraged to optimize continuous care provisioning. The evaluation of the building blocks on a realistic homecare monitoring use case demonstrates their applicability, usability and good performance. Further extending the available user interfaces for some tools is required to increase their adoption.

Agile neural expert system for managing basic education

Inadequate experts in managing resources at the lower level of education to enhance effective teaching and learning for quality education is a significant challenge in developing nations. Many basic schools lack basic educational resources such as sitting places and writing places for learners. Inadequate teaching and learning resources negatively affect the educational policies in a country. It is common to see the media projecting the challenges of a school lacking these resources. The use of an Expert System (ES) in Artificial Intelligence (AI) to assist in effective management is a necessity. In this paper, an agile neural expert system is proposed using differential equations with an initial value problem. The technique combines both rule-based and neural networks in handling the problem. The expertise of the Human Expert (HE) is used in a knowledge-based to assist in managing the resources in schools. This has been possible with the use of Data Mining (DM) techniques and modeling of projected population growth, affecting enrolment in schools and necessitating the provision of resources to cater to the growing population. For efficiency and effectiveness in planning, provision, and management of the resources, smart notification has been embedded in the system to monitor the availability and provision of the resources by prompting the various actors in the requisition, verification, validation, and approval of resources to be supplied to schools. The system proves a higher efficiency demonstrating speed in decision-making, accuracy in decisions and ease to use.

Improving the Financial Security of National Health Insurance using Cloud-Based Blockchain Technology Application

Since Bitcoin's success, there has been a greater emphasis on researching the use of blockchain in a wide range of applications, such as agriculture, education, government, voting systems, etc. This generation of Blockchain applications is termed blockchain 3.0. Blockchain technology provides enhanced security, auditability, privacy, accountability, and many more features over a centralized system. Fraud in insurance is an international problem affecting all insurance subdomains in both developed and developing countries. Fraud, corruption, and many other data-related problems are threatening the financial security of the National Health Insurance Scheme (NHIS) in Ghana and if not attended to, the core aims of the scheme to provide universal healthcare services will not be realized. Consequently, the objective of this work is to design and implement a blockchain-based solution to protect the NHIS from plummeting financially. This paper presents the conceptual view of the proposed system, sequence and use case diagrams, data management framework, smart notification system, and smart claim processing system. The system was evaluated using the DeLone & McLean Information Systems Success Model. It was used to validate the behavioural aspect of the system. The study discovered a significant influence of information quality and user satisfaction. On the contrary, system quality seems to have an almost significant influence on the use and user satisfaction of the proposed system.

Wi-Fi based Indoor Localization for Location-based Smart Notification

Indoor localization has been researched widely in the recent two decades due to its wide range of applications such as navigation, elder care, advertising. This work presents a utilization of indoor positioning for a location-based smart notification purposed, deployed in a meeting room booking application. Our localization method is based on Wi-Fi fingerprint, tailored to our application needs to alleviate the drawback of its tedious offline phase. The initial implementation is done with limited number of recorded locations. The testing shows that the meeting room booking application works well, with the localization detecting user’s location correctly aside from when poor signal condition occurs.

Development and evaluation of the HaptiWatch with a smart notification system

AbstractIn this study, we developed a new type of smartwatch, the HaptiWatch, which has notification functions that are not present in analog watches that lack a high‐resolution display. The HaptiWatch also has a priority‐filtering function that distinguishes notifications by their importance. Notification information is encoded as light and haptic pulses which allow users to recognize the type and importance of the notification without having to see the watch. To evaluate the user experience (UX) of the HaptiWatch's new notification system, a comparative study was conducted together with the notification system of the Samsung Galaxy Gear S3 Frontier, a well‐known smartwatch. The UX evaluation results indicate that the notification system of the HaptiWatch provides an experience that is comparable to that of the Gear S3.

IP Speaker with SIP and Smart Notification System

IP Speaker with SIP and Smart Notification System

A Smart Context-Aware Hazard Attention System to Help People with Peripheral Vision Loss.

Peripheral vision loss results in the inability to detect objects in the peripheral visual field which affects the ability to evaluate and avoid potential hazards. A different number of assistive navigation systems have been developed to help people with vision impairments using wearable and portable devices. Most of these systems are designed to search for obstacles and provide safe navigation paths for visually impaired people without any prioritisation of the degree of danger for each hazard. This paper presents a new context-aware hybrid (indoor/outdoor) hazard classification assistive technology to help people with peripheral vision loss in their navigation using computer-enabled smart glasses equipped with a wide-angle camera. Our proposed system augments users’ existing healthy vision with suitable, meaningful and smart notifications to attract the user’s attention to possible obstructions or hazards in their peripheral field of view. A deep learning object detector is implemented to recognise static and moving objects in real time. After detecting the objects, a Kalman Filter multi-object tracker is used to track these objects over time to determine the motion model. For each tracked object, its motion model represents its way of moving around the user. Motion features are extracted while the object is still in the user’s field of vision. These features are then used to quantify the danger using five predefined hazard classes using a neural network-based classifier. The classification performance is tested on both publicly available and private datasets and the system shows promising results with up to 90% True Positive Rate (TPR) associated with as low as 7% False Positive Rate (FPR), 13% False Negative Rate (FNR) and an average testing Mean Square Error (MSE) of 8.8%. The provided hazard type is then translated into a smart notification to increase the user’s cognitive perception using the healthy vision within the visual field. A participant study was conducted with a group of patients with different visual field defects to explore their feedback about the proposed system and the notification generation stage. The real-world outdoor evaluation of human subjects is planned to be performed in our near future work.

The design of smart notification on android gadget for academic announcement

In this article, we try to design the architecture of a smart notification system using an Android gadget for academic notification in college. Academic notification in colleges now utilizes bulletin boards and online media such as websites or social media. The problem faced is the high cost and resources required to deliver the academic notification. Another problem is whether the information delivered can be right to the students who need it. We proposed the architecture of a smart notification system that can reduce the cost, and the information delivered can be right on target to the students in need.

The Design of Notification System on Android Smartphone for Academic Announcement

Through this article, we try to propose the design of notification system that runs on the Android operating system. This notification will be used for the academic announcement in the campus environment. The current announcement system only depends on the web portal, phones, groups in social media or short message system. The use of web portals and phones still has many limitations. Our proposed notification system can meet the needs of academic announcement broadcast quickly and massively. In the end, this will cut the cost that stakeholders need to operate the academic announcement system in the campus environment. The design of smart notification system that we proposed in the future will be integrated with the academic information system.

ZIGBEE-BASED SMART FALL DETECTION AND NOTIFICATION SYSTEM WITH WEARABLE SENSOR (E-SAFE)

Fall is one of the serious health issues among elde rly population in Malaysia. In the event of a fall, a strong impact may be inflicted on the elderly causing severe injuries or even deat h. Another research by the National Institutes of H ealth found that 67% of elderly who fall and fail to seek help within 72 hours are unlikely to survive. Current Personal Emergency Res pond System (PERS) often employs the use of a manual emergency button. Howev er this approach may not be useful if the fall vict im become unconscious or even not be able to move to reach the emergency but ton. In addition, such as this approach also requir es more time and inadequate to notify and seek for immediate help. This paper atte mpts to design and implement a smart fall detection system for real time notification known as e-SAFE. This system will auto matically detect a fall and notifies the incident instantly to internal and external correspondence. The e-SAFE equipped with a wearable accelerometer sensor, microcontroller, ZigBee tran sceiver module and Global System for Mobile communications (GSM) devic e. The in-house correspondence will be notifies tho ugh the ZigBee technology, meanwhile the external correspondence will be notif ied through GSM. Once a fall has been detected by esystem, a Short Message Service (SMS) and an E-mail will be sent to predefined contacts which is stored in the system. This system will provide a path toward independent living for the elderly whil e keeping them save.