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The Internet of Things (IoT) is a complex ecosystem of connected devices that exchange data over a wired or wireless network and whose final aim is to provide services either to humans or machines. The IoT has seen rapid development over the past decade. The total number of installed connected devices is expected to grow exponentially in the near future, since more and more domains are looking for IoT solutions. As a consequence, an increasing number of developers are approaching IoT technology for the first time. Unfortunately, the number of IoT-related studies published every year is becoming huge, with the obvious consequence that it would be impossible for anyone to predict the time that could be necessary to find a paper talking about a given problem at hand. This is the reason why IoT-related discussions have become predominant in various practitioners’ forums, which moderate thousands of posts each month. The present paper’s contribution is twofold. First, it aims at providing a holistic overview of the heterogeneous IoT world by taking into account a technology perspective and a business perspective. For each topic taken into account, a tutorial introduction (deliberately devoid of technical content to make this document within the reach of non-technical readers as well) is provided. Then, a table of very recent review papers is given for each topic, as the result of a systematic mapping study.

Improving citizens' quality of life is a relevant research topic from long time. Several papers emphasized the geographical dimension of such a multidimensional problem. In a sub-category of those studies, the degree of satisfaction of the citizens’ needs is obtained by calculating the distance between the centroid of the polygon that expresses the boundary of the administrative district, within the city, where they live and the location of relevant public services in the area. An open issue is up to which geographical scale it is meaningful to push this approach. Our opinion is that the answer to such a question depends on the geography of the administrative units one refers to. So, the only way to know what to do consists in conducting a preliminary computation devoted to investigate the geometrical structure of the administrative units. In connection with this issue, our paper reports the findings of a case study regarding the three administrative levels of Italy.

In this paper, we focus on public buildings. They represent a relevant category of elements because of their intrinsic economic value and because their damage may cause human casualties as well. If the survey covers developed, large geographic areas, the number of buildings potentially at risk exposed is very high. Such numbers make the use of the available methods of building risk assessment highly time-consuming and, hence, inapplicable in the reality. To mitigate such an issue, we introduce a method that takes as input all the buildings standing over the study area and outputs a ranking about them according to their degree of exposure to the landslide hazard. The practitioners in mitigation can extract from the ranking the top-N buildings to look at. Then, they need to carry out the detailed risk assessment only for the buildings on the short list. This way the overall processing time required for the computation of the vulnerability, and hence of the risk, is reduced dramatically. The ranking method has been tested to assess the exposure to the landslide hazard of the buildings hosting public schools in the Abruzzo Region (center of Italy), a large area (11,000 km2) with 1,330,000 inhabitants. The results obtained from the case study show that the top-N buildings to look at are a very small fraction of the total number of buildings in the region.

There is a growing number of frail patients whose health conditions require constant monitoring by physicians. Unfortunately, the budget restrictions of hospitals and the concomitant decision that patients should stay home require that this monitoring is to be carried out remotely. Today, Internet of Things (IoT) wearables are the most promising technology solution for sensing patients’ physiological values 24/7. These measurements need to be stored permanently and then processed in order to provide support to physicians in charge of making real-time clinical decisions consistent with the patient’s health status. This paper elaborates on the combination of the IoT and DBMS technologies. In detail, a PostgreSQL relational database stores patient-generated health data (PGHD), while a set of SQL views generates standard summary statistical indicators.

Today, specialized software (called IoT platforms or, alternatively, IoT middleware) is available to build and manage IoT solutions from scratch, without having to write endless lines of code. Unfortunately, the selection of the IoT platform that best fits the requirements of the application to be developed is not trivial and may take a long time. The challenge comes from the huge number of candidates available today. The present work aims to relieve IT developers of the need to take charge of the IoT platform selection process. A systematic mapping study (SMS) was carried out. The final finding was that, at present, ThingsBoard is the most mature open-source IoT platform to be used for the prototyping of IoT applications without having to be an expert programmer.

This study proposes the adoption of the IoT technology for the home monitoring of the health status of frail patients. Such a solution is thought to be part of the forthcoming Italian COT; the latter is an organizational model which is devoted to integrate the current national healthcare network. The prevalent deployment model of IoT systems is the Cloud, which offers powerful services and unlimited storage/computing capacity on-demand; unfortunately, connecting smart devices to the Cloud poses severe issues. First of all, connected devices create large volumes of data, which will drive inevitably to performance and network congestion challenges. Secondly, there are security, bandwidth, and reliability concerns that make the Cloud-only solution not suitable for all the potential real-world applications. The Fog computing paradigm has been introduced to bridge the gap between the Cloud and IoT devices. This paper gives a twofold contribution: (a) a Cloud–Fog architecture is proposed using a three-tiers solution where the Fog computing layer constitutes the middle tier; (b) simulations have been carried out in order to compare Cloud–Fog computing as an alternative to the Cloud-only solution. The experimental results demonstrate a remarkable degradation of the latency in the first solution with respect to the second one. The measured benefit indicates that the best way to implement the COTs consists in placing inside them the fog layer mentioned above. The iFogSim open-source toolkit has been used to carry out the experiments.

Many scholars have reported that the adoption of Model Driven Engineering (MDE) in the industry is still marginal. Real-life case studies, completed with convincing empirical data about the quality of the developed source code, is an effective way to persuade the industry that the adoption of MDE brings an actual added value. This paper reports about the assessment of the quality of the code outputted by xGenerator: a Java technology platform for the development of enterprise Web applications, which implements the MDE paradigm. Two recent papers from Aniche and his colleagues were selected to carry out the measurements. The former study is about metrics and thresholds for MVC Web applications, while the latter presents a catalog of six smells tailored to MVC Web applications. A big merit of both of these proposals is that they fix the metric thresholds by taking into account the MVC software architecture. The results of the empirical assessment, carried out on a real-life project, proved that the quality of the code is high.

The need to protect critical infrastructures (for short called assets within this paper) arises because of the hazards they are exposed to. In this article, the hazard is represented by the landslides. The first part of the paper proposes a scientifically robust method for the identification of the top-N assets that can be modeled as “points” (mainly buildings). The developed method takes into account the slope of the terrain, the runout distance of the landslide and its trajectory. The latter is roughly estimated through the notion of linear regression line. The method is applied to a real case to carry out a preliminary validation of it. In the second part of the paper, it is formalized the problem of computing the ranking of assets that can be modeled as “lines” (e.g., highways, power lines, pipelines, railway lines, and so on, that cross a given territory). The problem is solved in three steps: (a) Segmentation (it “cuts” each route in segments), (b) Sampling (it extracts points from each segment), and (c) Calculation (it associates an exposure value to each extracted point and, then, computes the exposure of the various segments composing the routes). The computation of the exposure for the points is carried out by applying the method of the first part of the paper. Both rankings can be used by the local administrators as a conceptual tool for narrowing down a global problem to smaller, higher exposure, geographic areas where the management of the hazard is crucial.

Illegal buildings (IBs) are a dramatic problem in developing countries due to the population explosion, but, at the same time, they represent an unsolved issue in several states usually called advanced (as, for instance, Italy). To protect the environment, and hence, people, land authorities must respond to the challenge of IBs by demolishing them. However, in countries where the phenomenon is extended, it is indispensable to provide those figures with an IT tool that returns to them an order of demolition. Through remote sensing methods, suspicious buildings can be identified with a good approximation, but they are all ex aequo. The research summarized in this paper formalizes a two-steps method to deal with a specific category of IBs, namely, those that are close to rivers. These buildings are of special interest to land authorities because people living or simply working inside them are exposed to the flood hazard that each year claims many victims all over the world. The first step of the method computes the census of the IBs located close to rivers, while the second step computes the ranking of these buildings. The ranking may be used as the IBs demolition order. In the paper, it is also proposed the structure of a Spatial DataBase (briefly, SDB) that is suitable to store the input data necessary to solve the problem, as well as the final ranking. Spatial SQL queries against the SDB implement the proposed two-steps method. A real case study was carried out to make a preliminary validation of the method.

The effectiveness of disaster response depends on the correctness and timeliness of data regarding the location and the impact of the event. These two issues are critical when the data come from citizens’ tweets, since the automatic classification of disaster-related tweets suffers from many shortcomings. In this paper, we explore an approach based on participatory sensing (i.e., a subset of mobile crowdsourcing that emphasizes the active and intentional participation of citizens to collect data from the place where they live or work). We operate with the hypothesis of a “friendly world”, that is by assuming that after a calamitous event, in the survivors prevails the feeling of helping those who suffer. The extraction, from the Twitter repository, of the few tweets relevant to the event of interest has a long processing time. With the aggravating circumstance in the phase that follows a severe earthquake, the elaboration of tweets clashes with the need to act promptly. Our proposal allows a huge reduction of the processing time. This goal is reached by introducing a service and a mobile app, the latter is an intermediate tool between Twitter and the citizens, suitable to assist them to write structured messages that act as surrogates of tweets. The article describes the architecture of the software service and the steps involved in the retrieval, from the Twitter server, of the messages coming from citizens living in the places hit by the earthquake; moreover, it details the storage of those messages into a geographical database and their processing using SQL.

La crescente comunità di escursionisti si trova ciclicamente a dover affrontare il dilemma di quale percorso scegliere per la “prossima” escursione ricorrendo al Web per la ricerca di siti dedicati allo scopo, in apprezzabile aumento, ma non ancora consolidati nel supporto da offrire agli utenti nella fase in cui devono prendere la decisione di quale percorso sia più idoneo per loro. Il presente articolo propone una soluzione originale su questa delicata questione A GIS solution for the choiceof hiking trails The growing community of hikers is periodically faced with the dilemma of which path to choose for the "next" tour. The use of the Web to search sites for hiking, in noticeable increase, must be supported to better provide info to users, in the phase in which they must make the decision on which path is most suitable for them. This ar-ticle proposes an original solution to this sensitive issue.