Mirjami Jutila

An Adaptive Edge Router Enabling Internet of Things

The vision of future networking is that not only people but also all things, services, and media will be connected and integrated, creating an Internet of Everything (IoE). Internet-of-Things (IoT) systems aim to connect and scale billions of devices in various domains such as transportation, industry, smart home/city, medical services, and energy systems. Different wireless and wired technologies link sensors and systems together, through wireless access points, gateways, and routers that in turn connect to the web and cloud-based intelligence. IoT architectures make great demands on network control methods for the efficient management of massive amounts of nodes and data. Therefore, some of the clouds management tasks should be distributed around the edges of networked systems, utilizing fog computing to control and manage, e.g., network resources, quality, traffic prioritizations, and security. In this work, we present adaptive edge computing solutions based on regressive admission control (REAC) and fuzzy weighted queueing (FWQ) that monitor and react to network quality-of-service (QoS) changes within heterogeneous networks, and in a vehicular use case scenario utilizing IEEE 802.11p technology. These adaptive solutions are providing more stable network performance and optimizing the network path and resources.

Embedded fuzzy expert system for Adaptive Weighted Fair Queueing

This paper introduces an embedded fuzzy expert system for Adaptive Weighted Fair Queueing (AWFQ) located in the network traffic router to update weights for output queues. WFQ algorithm allows differentiated service for traffic classes according to Quality of Service (QoS) requirements. Link sharing and packet scheduling methods are the most critical factors when guaranteeing QoS. There are many different scheduling mechanisms but adequate and adaptive QoS aware scheduling solutions are still in a phase of development due to the rapid growth of multimedia in the Internet. The proposed AWFQ model in this work simplifies the link sharing to two service classes: one for UDP and another for TCP. The implementation of the model is based on adaptive change of weight coefficients that determine the amount of allowed bandwidth for the service class. New weight coefficients are calculated periodically on routers according to developed embedded fuzzy expert system. It is shown through simulations that the AWFQ model is more stable and reacts faster to different traffic states than the traditional WFQ scheduler. The embedded expert system adjusts the weights of AWFQ with two parameters that are based on the share of the UDP and TCP input traffic data rate and the change of the share of the UDP and TCP input data rate.

Wearable and mobile sensors connected to social media in human well-being applications

This paper introduces a concept based on monitoring human behavior using sensors with social media connectivity to distribute data and provide help to people in challenging situations. Together with its sub-concepts, it defines a framework for and specific aspects of communication in several application areas, in which sensors are used to track human behavior and measure the human physiological status. The thus gathered information is then shared via social media.Conventional information flow between a sensor and the social web is a one-way street, based on extraction of information or placement. Sensor data is shared on the social web on the users initiative. One-way flow is useful in many situations. More advanced functionality can be realized with bidirectional flow. Here, a sensor automatically invokes the social web to obtain relevant information that can influence the user. The social web can also take the initiator role and provide useful information for the sensor to act on.SEWEB concept was developed to provide help in challenging situations. Testing and evaluation of the concept was conducted using a schoolchildrens safety service application, and a related business model was created to discuss aspects linked to the concepts commercialization prospects. Safety of children and marginalization of youth are increasing problems in our modern society. Developing technologies, however, offer more possibilities for building safety solutions for children and teenagers. This paper describes a new concept of using sensors to monitor human behavior in combination with data processing and information transfer via different communication channels as well as different types of support the concept makes available. The concept utilizes the web and social media to create services and new business centered around different applications designed to support child safety in challenging situations and to prevent the marginalization of young people. This conceptual work involves different sub-concepts in the areas of information flow and connections, potential services and business potential. Some application areas will be introduced and discussed as specific cases demonstrating the features of the developed concept.

Implementation of a Wearable Sensor Vest for the Safety and Well-being of Children☆

Abstract This paper presents a prototype wearable vest for improving the safety and well-being of children in nurseries, daycare centres and primary schools. The safety vest is built around the LilyPad Arduino and Adafruit Flora platforms with Xbee radio module, GPS, temperature and accelerometer sensors. The vest will automatically gather and provide information about the location and well-being of the children. Teachers are able to receive alerts and notifications, e.g., when a child moves across certain restricted outdoor or indoor area. All the information gathered by the vest is made available through the web utilising Sensor Web Enable- ment (SWE) services to guarantee a standardised way to manage the data coming from multiple sources. The vest is part of a larger framework to provide digital safety applications and services for parents and teachers.

Safety services for children: a wearable sensor vest with wireless charging

Wearable sensors constitute an increasing market in providing various promising opportunities for improving and controlling safety issues for children in day care and schools. This paper presents the technological enablers and requirements for building a complete end-to-end energy-efficient safety system. Our work introduces a proof-of-concept for a wearable sensor vest with integrated wireless charging, designed to enhance the security of children. The wireless charging takes place in the ordinary repository for the vests, such as in a wardrobe or a coat rack, without requiring any specific actions from the user. The developed sensor vest provides information about the location and well-being of children, based on received signal strength indication, global positioning system, accelerometer, and temperature sensors. This paper also discusses the experiences of the “safety service for children” school pilot, which utilized various sensors with end-to-end applications. Piloting and technological implementations are based on a participatory study conducted among children, teachers, and parents, to gain important knowledge and understanding about the real user needs and service system usability requirements.

Improving the Well-Being and Safety of Children with Sensors and Mobile Technology

ABSTRACT The well-being and safety of children and young people are important aspects in all contexts of everyday life. In particular, a feeling of insecurity might be a problem when being alone. Bullying is also common among school-age children and teenagers. Hence, there is a great need for personalized support systems to resolve these problems. This article describes a new area of research in sensor and social web development to help indicate children’s insecurity in their daily environment. Deeper integration of sensors and the social web would allow us to foresee drastic changes in communities and new social–ethical scenarios will emerge.

Fuzzy Service classifier for QoS improvement

In this paper is introduced a FSC (Fuzzy Service Classification) algorithm. The algorithm adaptively change weight coefficients that determine the amount of allowed bandwidth for each service class in the outputs of routers. New weight coefficients are calculated periodically on routers. The proposed fuzzy model simplifies the link sharing to two service classes: one for UDP and another for TCP. It is shown through simulations that the fuzzy model is more stable and reacts faster to different traffic states than the traditional WFQ (weighted fair queueing) scheduler.