Enabling stream processing for people-centric IoT based on the fog computing paradigm

The world of machine-to-machine (M2M) communication is gradually moving from vertical single purpose solutions to multi-purpose and collaborative applications interacting across industry verticals, organizations and people - A world of Internet of Things (IoT). The dominant approach for delivering IoT applications relies on the development of cloud-based IoT platforms that collect all the data generated by the sensing elements and centrally process the information to create real business value. In this paper, we present a system that follows the Fog Computing paradigm where the sensor resources, as well as the intermediate layers between embedded devices and cloud computing datacenters, participate by providing computational, storage, and control. We discuss the design aspects of our system and present a pilot deployment for the evaluating the performance in a real-world environment. Our findings indicate that Fog Computing can address the ever-increasing amount of data that is inherent in an IoT world by effective communication among all elements of the architecture

An IoT-based solution for monitoring a fleet of educational buildings focusing on energy efficiency

Raising awareness among young people and changing their behaviour and habits concerning energy usage iskey to achieving sustained energy saving. Additionally, young people are very sensitive to environmental protection so raising awareness among children is much easier than with any other group of citizens. This work examinesways to create an innovative Information & Communication Technologies (ICT) ecosystem (including web-based, mobile, social and sensing elements) tailored specifically for school environments, taking into account both theusers (faculty, staff, students, parents) and school buildings, thus motivating and supporting young citizenś behavioural change to achieve greater energy efficiency. A mixture of open-source IoT hardware and proprietary platforms on the infrastructure level, are currently being utilized for monitoring a fleet of 18 educational buildings across 3 countries, comprising over 700 IoT monitoring points. Hereon presented is the system's high-level architecture, as well as several aspects of its implementation, related to the application domain of educational building monitoring and energy efficiency. The system is developed based on open-source technologies andservices in order to make it capable of providing open IT-infrastructure and support from different commercial hardware/sensor vendors as well as open-source solutions. The system presented can be used to develop and offer newapp-based solutions that can be used either for educational purposes or for managing the energy efficiency ofthebuilding. The system is replicable and adaptable to settings that may be different than the scenarios envisionedhere (e.g., targeting different climate zones), different IT infrastructures and can be easily extended to accommodate integration with other systems. The overall performance of the system is evaluated in real-world environment in terms of scalability, responsiveness and simplicity

iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs

Internet of Things Cloud: Architecture and Implementation

The Internet of Things (IoT), which enables common objects to be intelligent and interactive, is considered the next evolution of the Internet. Its pervasiveness and abilities to collect and analyze data which can be converted into information have motivated a plethora of IoT applications. For the successful deployment and management of these applications, cloud computing techniques are indispensable since they provide high computational capabilities as well as large storage capacity. This paper aims at providing insights about the architecture, implementation and performance of the IoT cloud. Several potential application scenarios of IoT cloud are studied, and an architecture is discussed regarding the functionality of each component. Moreover, the implementation details of the IoT cloud are presented along with the services that it offers. The main contributions of this paper lie in the combination of the Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT) servers to offer IoT services in the architecture of the IoT cloud with various techniques to guarantee high performance. Finally, experimental results are given in order to demonstrate the service capabilities of the IoT cloud under certain conditions.Comment: 19pages, 4figures, IEEE Communications Magazin