Many devices and solutions for remote electrocardiogram (ECG) monitoring have been proposed in the literature. These solutions typically have a large marginal cost per added sensor and are not seamlessly integrated with other smart home solutions. Here, we propose an ECG remote monitoring system that is dedicated to non-technical users in need of long-term health monitoring in residential environments and is integrated in a broader Internet-of-Things (IoT) infrastructure. Our prototype consists of a complete vertical solution with a series of advantages with respect to the state of the art, considering both the prototypes with integrated front end and prototypes realized with off-the-shelf components: 1) ECG prototype sensors with record-low energy per effective number of quantized levels; 2) an architecture providing low marginal cost per added sensor/user; and 3) the possibility of seamless integration with other smart home systems through a single IoT infrastructure

The customer domain of the smart grid natu- rally blends with smart home and smart building systems, but typical proposed approaches are “distributor-centric” rather than “customer-centric,” undermining user acceptance, and are often poorly scalable. To solve this problem, we propose a detailed architecture and an implementation of a “last-meter” smart grid—the portion of the smart grid on customer premises—embedded in an internet-of-things (IoT) platform. Our approach has four aspects of novelty and advantages with respect to the state of the art: 1) seamless integration of smart grid with smart home applications in the same infrastructure; 2) data gathering from heterogeneous sensor communication protocols; 3) secure and customized data access; and 4) univocal sensor and actuator mapping to a common abstraction layer on which additional concurrent applications can be built. A demonstrator has been built and tested with purposely-developed ZigBee smart meters and gateways, a distributed IoT server, and a flexible user interface

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The keystone of many applications associated to the vision of the Internet of Things is a distributed measurement and data acquisition system. Its design represents a major challenge, because it must enable concurrent measurement of different signals, with heterogeneous sensors and communication protocols. It must also be secure and scalable (in the sense of low marginal cost of adding new features and sensors). We propose the architecture of such a system and demonstrate two different use cases: a distributed system for electric power metering, and a wearable ECG monitoring system for multiple patients. We show that our proposed solution is flexible in terms of measured quantities, and can easily adapt to different data rates. In addition, it allows us to reach record performance in terms of energy consumption per effective number of quantization levels, as we demonstrate in the case of ECG sensors.