An IoT-aware AAL System to Capture Behavioral Changes of Elderly People

The ageing of population is a phenomenon that is affecting the majority of developed countries around the world and will soon affect developing economies too. In recent years, both industry and academia are focused on the development of several solutions aimed to guarantee a healthy and safe lifestyle to the elderly. In this context, the behavioral analysis of elderly people can help to prevent the occurrence of Mild Cognitive Impairment (MCI) and frailty problems. The innovative technologies enabling the Internet of Things (IoT) can be used in order to capture personal data for automatically recognizing changes in elderly people behavior in an unobtrusive, low-cost and low-power modality. This work aims to describe the ongoing activities within the City4Age project, funded by the Horizon 2020 Programme of the European Commission, mainly focused on the use of IoT technologies to develop an innovative AAL system able to capture personal data of elderly people in their home and city environments. The proposed architecture has been validated through a proof-of-concept focused mainly on localization issues, collection of ambient parameters, and user-environment interaction aspects

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

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

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

A Smart IoT-Aware System For Crisis Scenario Management

In most dangerous events, involving many people in large buildings, rescue workers need to intervene in a timely and targeted manner in order to help most number of people and secure the environments without wasting resources. This work presents an Internet of Things(IoT)-based framework, aiming at monitoring environmental parameters in order to alert rescuers when they exceed some alarm thresholds. A hardware infrastructure driven by a software layer adds flexibility and adaptability to the Complex Event Processing engine and to a rule engine-based reflective middleware that manages and analyzes raw data in conjunction with a knowledge base modeling the application domain

Carbon-Fiber-Recycling Strategies: A Secondary Waste Stream Used for PA6,6 Thermoplastic Composite Applications

With a view to achieving sustainable development and a circular economy, this work focused on the possibility to valorize a secondary waste stream of recycled carbon fiber (rCF) to produce a 3D printing usable material with a PA6,6 polymer matrix. The reinforcing fibers implemented in the research are the result of a double-recovery action: starting with pyrolysis, long fibers are obtained, which are used to produce non-woven fabrics, and subsequently, fiber agglomerate wastes obtained from this last process are ground in a ball mill. The effect of different amounts of reinforcement at 5% and 10% by weight on the mechanical properties of 3D-printed thermoplastic composites was investigated. Although the recycled fraction was successfully integrated in the production of filaments for 3D printing and therefore in the production of specimens via the fused deposition modeling technique, the results showed that fibers did not improve the mechanical properties as expected, due to an unsuitable average size distribution and the presence of a predominant dusty fraction ascribed to the non-optimized ball milling process. PA6,6 + 10 wt.% rCF composites exhibited a tensile strength of 59.53 MPa and a tensile modulus of 2.24 GPa, which correspond to an improvement in mechanical behavior of 5% and 21% compared to the neat PA6,6 specimens, respectively. The printed composite specimens loaded with the lowest content of rCF provided the greatest improvement in strength (+9% over the neat sample). Next, a prediction of the "optimum" critical length of carbon fibers was proposed that could be used for future optimization of recycled fiber processing

Performance Evaluation of end-to-end security protocols in an Internet of Things

Wireless Sensor Networks are destined to play a fundamental role in the next-generation Internet, which will be characterized by the Machine-to-Machine paradigm, according to which, embedded devices will actively exchange information, thus enabling the development of innovative applications. It will contribute to assert the concept of Internet of Things, where end-to-end security represents a key issue. In such context, it is very important to understand which protocols are able to provide the right level of security without burdening the limited resources of constrained networks. This paper presents a performance comparison between two of the most widely used security protocols: IPSec and DTLS. We provide the analysis of their impact on the resources of embedded devices. For this purpose, we have modified existing implementations of both protocols to make them properly run on our hardware platforms, and we have performed an extensive experimental evaluation study. The achieved results are not a consequence of a classical simulation campaign, but they have been obtained in a real scenario that uses software and hardware typical of the current technological developments. Therefore, they can help network designers to identify the most appropriate secure mechanism for end-to-end IP communications involving constrained devices

Inside the history of Italian coloring industries. An investigation of ACNA dyes through a novel analytical protocol for synthetic dye extraction and characterization

The introduction of synthetic dyes completely changed the industrial production and use of colorants for art materials. From the synthesis of the first synthetic dye, mauveine, in 1856 until today, artists have enjoyed a wider range of colors and selection of chemical properties than was ever available before. However, the introduction of synthetic dyes introduced a wider variety and increased the complexity of the chemical structures of marketed dyes. This work looks towards the analysis of synthetically dyed objects in heritage collections, applying an extraction protocol based on the use of ammonia, which is considered favorable for natural anthraquinone dyes but has never before been applied to acid synthetic dyes. This work also presents an innovative cleanup step based on the use of an ion pair dispersive liquid–liquid microextraction for the purification and preconcentration of historical synthetic dyes before analysis. This approach was adapted from food science analysis and is applied to synthetic dyes in heritage science for the first time in this paper. The results showed adequate recovery of analytes and allowed for the ammonia-based extraction method to be applied successfully to 15 samples of suspected azo dyes from the Azienda Coloranti Nazionali e Affini (ACNA) synthetic dye collection, identified through untargeted HPLC-HRMS analyses

New advances in dye analyses. In situ gel-supported liquid extraction from paint layers and textiles for SERS and HPLC-MS/MS Identification

To date, it is still not possible to obtain exhaustive information about organic materials in cultural heritage without sampling. Nonetheless, when studying unique objects with invaluable artistic or historical significance, preserving their integrity is a priority. In particular, organic dye identification is of significant interest for history and conservation research, but it is still hindered by analytes’ low concentration and poor fastness. In this work, a minimally invasive approach for dye identification is presented. The procedure is designed to accompany noninvasive analyses of inorganic substances for comprehensive studies of complex cultural heritage matrices, in compliance with their soundness. Liquid extraction of madder, turmeric, and indigo dyes was performed directly from paint layers and textiles. The extraction was supported by hydrogels, which themselves can undergo multitechnique analyses in the place of samples. After extraction, Ag colloid pastes were applied on the gels for SERS analyses, allowing for the identification of the three dyes. For the HPLC-MS/MS analyses, re-extraction of the dyes was followed by a clean-up step that was successfully applied on madder and turmeric. The colour change perceptivity after extraction was measured with colorimetry. The results showed ΔE values mostly below the upper limit of rigorous colour change, confirming the gentleness of the procedure

A Web-based Software System for Behavior Analysis of Laboratory Animals

The analysis of locomotion in laboratory animals plays a crucial role in many scientific research areas. In fact, important information on animals’ behavior and their reaction to a particular stimulus is deduced from a careful analysis of their movements. The techniques commonly adopted to support such analysis have many limitations, which make the related systems particularly ineffective. On the one hand, the human observation and annotation process is strongly observer-dependent and expensive in terms of time and efforts. On the other hand, the use of more sophisticated systems based on video recordings and recognition algorithms is very expensive and complex. In order to face this challenge, this paper presents a tracking solution based on passive Radio Frequency Identification (RFID) technology in Ultra High Frequency (UHF) band, allowing the tracking of laboratory animals with a high accuracy. The overall solution consists of a hybrid system including hardware and software components. In particular, in this paper, the attention is focused on the software component as the hardware has already been described in previous works. The software component is a Web-oriented solution that offers a complete 2D and 3D information tool including reports, dashboards, and tracking graphs. The proposed solution was widely tested using twelve laboratory mice and compared with an automated video-tracking software (i.e., EthoVision) in order to demonstrate its effectiveness and reliability. The obtained results have demonstrated that the proposed solution is able to correctly detect and reconstruct the events occurring in the animals’ cage, and to offer a complete and user-friendly tool to support researchers in behavioral analysis of small laboratory animals