IoT Notifications: from disruption to benefit - Architectures for the future of notifications in the IoT

The growing number of mobile and IoT devices able to generate and show incoming notifications is fostering the spread of notifications in people lives. Nonetheless, although users are getting used to them, their presence is not always perceived as a benefit by recipients. With the aim of improving user experience with notifications, two different approaches are presented in this dissertation. The former acts at the distribution level, i.e., notifications are intercepted and then a system decides if, when, and how to show them; while the latter acts at the design level, i.e., notifications and their distribution strategies are designed with the aim of reducing user disruption and exploiting all the benefits that the availability of multiple devices could bring. An IoT architecture is proposed for each approach: the Smart Notification System that relies on machine learning algorithms to adequately manage incoming notifications, and the XDN (Cross-Device Notification) framework that assists developers in creating cross-device notifications by scripting. The modular nature of both architectures allowed the simultaneous development and test of different independent but compatible subsystems and their exploitation in preliminary deployment sessions. The results, feedbacks and lessons learned from such sessions can foster the development of future solutions in the IoT notifications field and related domains

Al2O3/ZrO2/Y3Al5O12 composites. A high-temperature mechanical characterization

An Al2O3/5 vol%·ZrO2/5 vol%·Y3Al5O12 (YAG) tri-phase composite was manufactured by surface modification of an alumina powder with inorganic precursors of the second phases. The bulk materials were produced by die-pressing and pressureless sintering at 1500 °C, obtaining fully dense, homogenous samples, with ultra-fine ZrO2 and YAG grains dispersed in a sub-micronic alumina matrix. The high temperature mechanical properties were investigated by four-point bending tests up to 1500 °C, and the grain size stability was assessed by observing the microstructural evolution of the samples heat treated up to 1700 °C. Dynamic indentation measures were performed on as-sintered and heat-treated Al2O3/ZrO2/YAG samples in order to evaluate the micro-hardness and elastic modulus as a function of re-heating temperature. The high temperature bending tests highlighted a transition from brittle to plastic behavior comprised between 1350 and 1400 °C and a considerable flexural strength reduction at temperatures higher than 1400 °C; moreover, the microstructural investigations carried out on the re-heated samples showed a very limited grain growth up to 1650 °C

Home delivery services: innovations and emerging needs

The increasing amount of small-sized shipments and their frequency variation, due to the growth of e-commerce, pose a great challenge to logistics service providers. At the same time, new technologies and innovations are being developed with the aim of increasing the efficiency of logistics service provider, as much as foster the creation of new enterprises and business models in the home delivery sector. The aim of this paper is to provide an exploratory analysis of the fit between existing home delivery innovative services, requirements, and issues that users might have. To do so, we review the main features of innovative services and we compare them with the findings from an online survey. For each service, we identify the value propositions, and the issues the service aims to address. In particular, four innovative services are reviewed. Through the online survey, we identify user’s habits, requirements and perceptions regarding the effectiveness and features of the innovative services

XDN: Cross-Device Framework for Custom Notifications Management

With the increase of connected devices and online services, and recently IoT devices, the number of notifications received by every person is growing. The importance of notifications, as they become part of people’s lives, often depends on various factors that can differently influence the reaction and the disruption of recipients. For this reason, the generation and the distribution of notifications has been gaining importance in the design of new applications, services, and smart devices. Nowadays, developers have not yet fully exploited all the advantages that the availability of multiple devices could bring in the customization and the distribution of notifications, e.g., exploiting a cross-device approach. This paper presents XDN (Cross Device Notification), a framework to assist developers in creating cross-device notifications by scripting. The XDN architecture includes: a library to enable developers to design personalized notifications to be distributed among ad-hoc networks of IoT/mobile devices; a GUI to assist developers in implementing and testing (through a simulator) notification strategies; a server-side runtime environment; and an XDN IoT/mobile library for device support. We discuss the requirements for cross device notification systems, and we present the features of the XDN framework, in particular from the point of view of developer advantages, validated through different scenarios

SmartBike: an IoT Crowd Sensing Platform for Monitoring City Air Pollution

In recent years, the Smart City concept is emerging as a way to increase efficiency, reduce costs, and improve the overall quality of citizen life. The rise of Smart City solutions is encouraged by the increasing availability of Internet of Things (IoT) devices and crowd sensing technologies. This paper presents an IoT Crowd Sensing platform that offers a set of services to citizens by exploiting a network of bicycles as IoT probes. Based on a survey conducted to identify the most interesting bike-enabled services, the SmartBike platform provides: real time remote geo-location of users’ bikes, anti-theft service, information about traveled route, and air pollution monitoring. The proposed SmartBike platform is composed of three main components: the SmartBike mobile sensors for data collection installed on the bicycle; the end-user devices implementing the user interface for geo-location and anti-theft; and the SmartBike central servers for storing and processing detected data and providing a web interface for data visualization. The suitability of the platform was evaluated through the implementation of an initial prototype. Results demonstrate that the proposed SmartBike platform is able to provide the stated services, and, in addition, that the accuracy of the acquired air quality measurements is compatible with the one provided by the official environmental monitoring system of the city of Turin. The described platform will be adopted within a project promoted by the city of Turin, that aims at helping people making their mobility behavior more sustainable

A Smart and Secure Logistics System Based on IoT and Cloud Technologies

Recently, one of the hottest topics in the logistics sector has been the traceability of goods and the monitoring of their condition during transportation. Perishable goods, such as fresh goods, have specifically attracted attention of the researchers that have already proposed different solutions to guarantee quality and freshness of food through the whole cold chain. In this regard, the use of Internet of Things (IoT)-enabling technologies and its specific branch called edge computing is bringing different enhancements thereby achieving easy remote and real-time monitoring of transported goods. Due to the fast changes of the requirements and the difficulties that researchers can encounter in proposing new solutions, the fast prototype approach could contribute to rapidly enhance both the research and the commercial sector. In order to make easy the fast prototyping of solutions, different platforms and tools have been proposed in the last years, however it is difficult to guarantee end-to-end security at all the levels through such platforms. For this reason, based on the experiments reported in literature and aiming at providing support for fast-prototyping, end-to-end security in the logistics sector, the current work presents a solution that demonstrates how the advantages offered by the Azure Sphere platform, a dedicated hardware (i.e., microcontroller unit, the MT3620) device and Azure Sphere Security Service can be used to realize a fast prototype to trace fresh food conditions through its transportation. The proposed solution guarantees end-to-end security and can be exploited by future similar works also in other sectors

An Unsupervised and Non-Invasive Model for Predicting Network Resource Demands

During the last decade, network providers are faced by a growing problem regarding the distribution of bandwidth and computing resources. Recently, the mobile edge computing paradigm was proposed as a possible solution, mainly in consideration of the provided possibility of transferring service demands at the edge of the network. This solution heavily relies on the dynamic allocation of resources, depending on the user needs and network connection, therefore it becomes essential to correctly predict user movements and activities. This paper proposes an unsupervised methodology to define meaningful user locations from noninvasive user information, captured by the user terminal with no computing or battery overhead. The data is analyzed through a conjoined clustering algorithm to build a stochastic Markov chain to predict the users’ movements and their bandwidth demands. Such a model could be used by network operators to optimize network resources allocation. To evaluate the proposed methodology, we tested it on one of the largest public community’s labeled mobile and sensor dataset, developed by the “CrowdSignals.io” initiative, and we present positive and promising results concerning the prediction capabilities of the model

Improving the effectiveness of SQL learning practice: a data-driven approach

Most engineering courses include fundamental practice activities to be performed by students in computer labs. During lab sessions, students work on solving exercises with the help of teaching assistants, who often have a hard time for guaranteeing a timely, optimized, and “democratic” support to everybody. This paper presents a learning environment to improve the experience of the lab sessions participants, both the students and the teaching assistants. In particular, the environment was designed, implemented, and experimented in the context of a database course. The application designed to support the learning environment stores all the events occurring during a SQL practice lab, i.e., task progression, query submissions, error feedback, assistance requests and interventions, and it provides information useful both for use on-the-fly and for later analysis. Thanks to the analysis of these data, the application dynamically provides teaching assistants with a graphical interface highlighting where assistance is most needed, by considering different factors such as the progression rate, the percentage of correct solutions, and the difficulties in solving the current exercise. Furthermore, the stored data allow teachers later on to analyze and to interpret the behavior of the students during the lab, and to have insights on their main mistakes and misconceptions. After describing the environment, the interfaces, and the approaches used to identify the students’ teams that need timely assistance, the paper presents the results of different analyses performed using the collected data, to help the teacher better understand students’ educational needs

Fast-prototyping Approach to Design and Validate Architectures for Smart Home

The Internet of Things has contributed to make smarter houses and buildings in the last decades. Different existing works already integrate IoT technologies in homes, but end-user needs continuously change and researchers must face this challenge in identifying platforms to fast prototype solutions satisfying these new needs. This paper presents a solution that demonstrates how well-known fast-prototyping technologies like Node-RED, IBM Watson, Telegram, Raspberry Pi 4, and secured MQTT can contribute to develop complex systems facing the challenge. The selected tools are used within a smart home context to support features inspired by people needs and allow users to: a) consult real time conditions (i.e., temperature, humidity, gas), b) remotely manage lights, c) save energy through a light management system based on user movements, d) remotely monitor the house through dedicated webcams, e) generate warning notifications in case of danger. Users can interact with the systems through a web Node-RED dashboard and a Telegram bot. Differently from existing works, the feasibility of the implemented system and the efficacy of the exploited platforms are demonstrated through a running scenario extracted from a consolidated study on user needs in smart homes. The performed experiment can facilitate the fast prototyping of new solutions

IoT-Aware Architecture to Guarantee Safety of Maintenance Operators in Industrial Plants

One of the most important factors that influence people’s daily lives and their well-being at work is the so-called “worker safety”. Different literature works demonstrated the positive effects on worker mood and well-being brought by the awareness of being in a safe environment and, consequently, less prone to accidents. Every working environment should guarantee safety protection to employees and operators both in normal operations and extraordinary duties (e.g., maintenance operations), however, the industrial domain is the one that is more exposed to risks for workers. Different technologies already accomplished such requirements in “normal” operations, nonetheless, the literature still lacks solutions to also monitor and guide operators during exceptional and dangerous operations (e.g., maintenance). The combination of IoT and Industry 4.0 can guide the research toward the resolution of the maintenance-related exposed problems. This paper proposes an IoT-aware architecture for the industrial domain to support maintenance operators. It was designed to guide them step by step while real-time monitoring plant, machinery, and other employees working in the same area. During the maintenance procedure, the operator is guided in the proper execution of every single step required by maintenance and an autonomous IoT system monitors the status of the different parts of the plants and machinery to, then, authorize and show, the next steps foreseen in the maintenance process. To test the feasibility and usefulness of the proposed system, a prototype was developed and functionally tested through the exploitation of a machinery simulator and a real lathe machine