Tomi Westerlund

Fog Computing in Healthcare Internet of Things: A Case Study on ECG Feature Extraction

Internet of Things technology provides a competent and structured approach to improve health and wellbeing of mankind. One of the feasible ways to offer healthcare services based on IoT is to monitor humans health in real-time using ubiquitous health monitoring systems which have the ability to acquire bio-signals from sensor nodes and send the data to the gateway via a particular wireless communication protocol. The real-time data is then transmitted to a remote cloud server for real-time processing, visualization, and diagnosis. In this paper, we enhance such a health monitoring system by exploiting the concept of fog computing at smart gateways providing advanced techniques and services such as embedded data mining, distributed storage, and notification service at the edge of network. Particularly, we choose Electrocardiogram (ECG) feature extraction as the case study as it plays an important role in diagnosis of many cardiac diseases. ECG signals are analyzed in smart gateways with features extracted including heart rate, P wave and T wave via a flexible template based on a lightweight wavelet transform mechanism. Our experimental results reveal that fog computing helps achieving more than 90% bandwidth efficiency and offering low-latency real time response at the edge of the network.

LISA: Lightweight Internet of Things Service Bus Architecture☆

A critical challenge faced in Internet of Things (IoT) is the heterogeneous nature of its nodes from the network protocol and platform point of view. To tackle the heterogeneous nature, we introduce a distributed and lightweight service bus, LISA, which fits into network stack of a real-time operating system for constrained nodes in IoT. LISA provides an application programming interface for developers of IoT on tiny devices. It hides platform and protocol variations underneath it, thus facilitating interoperability challenges in IoT implementations. LISA is inspired by the Network on Terminal Architecture (NoTA), a service centric open architecture by Nokia Research Center. Unlike many other interoperability frameworks, LISA is designed specifically for resource constrained nodes and it provides essential features of a service bus for easy service oriented architecture implementation.

PARS — An efficient congestion-Aware Routing method for Networks-on-Chip

The performance of NoCs (Networks-On-Chip) highly relies on the routing algorithm. Despite the higher implementation complexity compared with deterministic routing, adaptive routing has several merits, such as lower latency, higher throughput and better fault-tolerance performance. Most of the existing adaptive routing algorithms are based on the comparison of the horizontal and vertical congestion status in the network. However the performance of adaptive routing schemes suffers from the inadequate global congestion information. To address this issue, we proposed a novel routing algorithm with a congestion aware subnetwork to obtain more accurate non-local congestion information. This subnetwork will propagate the congestion information along the paths directly towards the destination. To find a less congested path, PARS (Path-Aware Routing Scheme) uses the congestion information of paths in a straight direction towards the destination rather than local congestion information. The simulation results reveal that the new presented scheme can offer better performance under different traffic profiles with a small hardware overhead.

Customizing 6LoWPAN networks towards Internet-of-Things based ubiquitous healthcare systems

Embedded devices with enhanced communication capabilities, Internet of Things (IoT), are able to perform a wide variety of different tasks at present. One rapidly increasing application domain is healthcare. In this paper, we present an IoT-based architecture and system implementation for healthcare applications. The presented IoT-based system provides a cost-effective and easy way to analyze and monitor, either remotely or on the spot, real-time health data such as Electrocardiogram (ECG) and Electromyography (EMG) data. Health data is transmitted by utilizing IPv6 over low power wireless area networks (6LoWPAN). Our efficient customization of the 6LoWPAN network for health data provides energy efficient and reliable transmission in different scenarios that is required in several healthcare applications.

Pervasive health monitoring based on Internet of Things: Two case studies

With the continuous evolution of wireless sensor networks and Internet of Things (IoT) various aspects of life will benefit. IoT based pervasive healthcare system has potential to provide error free medical data and alerting system in critical conditions with continuous monitoring. The system will minimize the need of dedicated medical personnel for patient monitoring and help the patients to lead a normal life besides providing them with high quality medical service. In this paper, we provide the implementation of IoT-based architectures for remote health monitoring based on two popular wireless technologies, Wi-Fi and ZigBee. We analyse the two architectures with the aim of identifying their pros and cons and discuss suitability of mentioned wireless communication technologies for different healthcare application domains.

IoT-based fall detection system with energy efficient sensor nodes

Fall needs to be attentively considered due to its highly frequent occurrence especially with old people — up to one third of 65 and above year-old people around the world are risk of being injured due to falling. Furthermore, fall is a direct or indirect factor causing severe traumas such as brain injuries or bone fractures. However, timely medical attention might help to avoid serious consequences from a fall. A viable solution to solve this is an IoT-based system which takes advantage of wireless sensor networks, wearable devices, Fog and Cloud computing. To deliver sufficient degree of reliability, wearable devices working at the core of a fall detection system, are required to work for prolonged period of time. In this paper we investigate energy consumption of sensor nodes in an IoT-based fall detection system and present a design of a customized sensor node. In addition, we compare the customized sensor node with other sensor nodes, built on general purpose development boards. The results show that sensor nodes based on delicate customized devices are more energy efficient than the others based on general purpose devices while considering identical specification of micro-controller and memory capacity. Furthermore, our customized sensor node with energy efficiency selections can operate continuously up to 35 hours.

LISA 2.0: lightweight internet of things service bus architecture using node centric networking

Internet of things (IoT) technologies are advancing rapidly and a wide range of physical networking alternatives, communication standards and platforms are introduced. However, due to differences in system requirements and resource constraints in devices, there exist variations in these technologies, standards, and platforms. Consequently, application silos are formed. In contrast to the freedom of choice attained by a range of options, the heterogeneity of the technologies is a critical interoperability challenge faced by IoT systems. Moreover, IoT is also limited to address new requirements that arise due to the nature of the majority of smart devices. These requirements, such as mobility and intermittent availability, are hardly satisfied by the current IoT technologies following the end-to-end model inherited from the Internet. This paper introduces a lightweight, distributed, and embedded service bus called LISA which follows a Node Centric Networking architecture. LISA is designed to provide interoperability for resource-constrained devices in IoT. It also enables a natural way of embracing the new IoT requirements, such as mobility and intermittent availability, through node centric networking. LISA provides a simple application programming interface for developers, hiding the variations in platform, protocol or physical network, thus facilitating interoperability in IoT systems. LISA is inspired by network on terminal architecture (NoTA), a service centric open architecture originated by Nokia Research Center. Our extensive experimental results show the efficiency and scalability of LISA in providing a lightweight interoperability for IoT systems.

Fault tolerant and scalable IoT-based architecture for health monitoring

A novel Internet of Things based architecture supporting scalability and fault tolerance for healthcare is presented in this paper. The wireless system is constructed on top of 6LoWPAN energy efficient communication infrastructure to maximize the operation time. Fault tolerance is achieved via backup routing between nodes and advanced service mechanisms to maintain connectivity in case of failing connections between system nodes. The presented fault tolerance approach covers many fault situations such as malfunction of sink node hardware and traffic bottleneck at a node due to a high receiving data rate. A method for extending the number of medical sensing nodes at a single gateway is presented. A complete system architecture providing a quantity of features from bio-signal acquisition such as Electrocardiogram (ECG), Electroencephalography (EEG), and Electromyography (EMG) to the representation of graphical waveforms of these gathered bio-signals for remote real-time monitoring is proposed.

Leveraging Fog Computing for Healthcare IoT

Developments in technology have shifted the focus of medical practice from treating a disease to prevention. Currently, a significant enhancement in healthcare is expected to be achieved through the Internet of Things (IoT). There are various wearable IoT devices that track physiological signs and signals in the market already. These devices usually connect to the Internet directly or through a local smart phone or a gateway. Home-based and in hospital patients can be continuously monitored with wearable and implantable sensors and actuators. In most cases, these sensors and actuators are resource constrained to perform computing and operate for longer periods. The use of traditional gateways to connect to the Internet provides only connectivity and limited network services. With the introduction of the Fog computing layer, closer to the sensor network, data analytics and adaptive services can be realized in remote healthcare monitoring. This chapter focuses on a smart e-health gateway implementation for use in the Fog computing layer, connecting a network of such gateways, both in home and in hospital use. To show the application of the services, simple healthcare scenarios are presented. The features of the gateway in our Fog implementation are discussed and evaluated.

Low-cost fog-assisted health-care IoT system with energy-efficient sensor nodes

A better lifestyle starts with a healthy heart. Unfortunately, millions of people around the world are either directly affected by heart diseases such as coronary artery disease and heart muscle disease (Cardiomyopathy), or are indirectly having heart-related problems like heart attack and/or heart rate irregularity. Monitoring and analyzing these heart conditions in some cases could save a life if proper actions are taken accordingly. A widely used method to monitor these heart conditions is to use ECG or electrocardiography. However, devices used for ECG are costly, energy inefficient, bulky, and mostly limited to the ambulatory environment. With the advancement and higher affordability of Internet of Things (IoT), it is possible to establish better health-care by providing real-time monitoring and analysis of ECG. In this paper, we present a low-cost health monitoring system that provides continuous remote monitoring of ECG together with automatic analysis and notification. The system consists of energy-efficient sensor nodes and a fog layer altogether taking advantage of IoT. The sensor nodes collect and wirelessly transmit ECG, respiration rate, and body temperature to a smart gateway which can be accessed by appropriate care-givers. In addition, the system can represent the collected data in useful ways, perform automatic decision making and provide many advanced services such as real-time notifications for immediate attention.