Typical mountain Search and Rescue (SaR) operations require the localization of the persons involved in accidents in harsh environments. ARVA and RECCO are the current standards for the localization in snowy environments although their radio range is limited to some tens of meters. In this paper, we prove by experimental results that the Long Range (LoRa) Low-Power Wide-Area Network (LPWAN) technology is very promising for SaR applications due to its extended radio range. A LoRa-based system for SaR operations is presented and analyzed. The localization of the persons is obtained through an algorithm based on path loss measurements. Radio path loss models of body-worn LoRa devices in harsh mountain environments are derived by measurements. We observed that, although the communication range of LoRa decreases from kilometres to hundreds of meters in the tested environments, at least 50% of the transmitted packets can be received at distances about five times greater than those achievable with golden standard technologies such as ARVA. The performances of the considered localization algorithm are analyzed on the basis of the collected data. The achievable accuracy is in the order of meters around the true position for a relatively large number of available path loss measurements. Lastly, we propose and detail a LoRa-based system for SaR operations. .

The emerging fourth industrial revolution is revolutionizing the food industry, which has historically been plagued by food waste and contamination. Several internet-of-things (IoT) technologies have been proposed for optimizing processes and reducing costs while improving health conditions and safety in food consumption. Among them, radiofrequency identification (RFID) has been considered from the beginning a key instrument, especially in food logistics and management. Many contributions and case studies from academia and industry demonstrated the strategic role and the impact on existing and future paradigms of food. The literature analysis in the present work suggests a growing interest in RFID to implement optimization procedures for food management and control. This review describes RFID employment in three pillars of the Fourth Generation of the Food Industry (FI4.0): Logistics, Sensing, and Green RFID. The logistics one comprises the most mature applications for RFID, such as cold-chain monitoring or product tracking. Food sensing, instead, is currently the most attractive research area for both industry and academia, so researchers are focusing their attention on detecting physical and chemical parameters through direct and indirect sensing approaches. Furthermore, the ever-increasing amount of electronic waste motivated the research community to provide sustainable tags to establish Green RFID devices. According to this literature review, RFID can foster the fourth industrial revolution in food, especially considering the emerging synergy with artificial intelligence and biodegradable/resorbable materials.

Due to the ongoing COVID-19 pandemic, the use of Filtering Facepiece Respirators (FFRs) is increasingly widespread. Since the masks wetness can reduce its filtering capabilities, the World Health Organization advises to replace the FFRs if they become too damp, but, currently, there is no practical way to monitor the masks wetness. A low-cost moisture sensor placed inside the FFRs could discriminate a slightly damp mask from a wet one which must be replaced. In this paper, a RadioFrequency Identification (RFID) tag exploiting an auto-tuning microchip for humidity sensing is designed and tested during an ordinary working day and a physical exercise. The tag returns about 1 unit of the digital metric every 3 milligrams of water generated by breathing and sweating, and it can identify excessively wet masks from commonly used ones.

The COVID-19 pandemic drastically changed our way of living. To minimize life losses, multi-level strategies requiring collective efforts were adopted while waiting for the vaccines’ rollout. The management of such complex processes has taken benefit from the rising framework of the Internet of Things (IoT), and particularly the Radiofrequency Identification (RFID) since it is probably the most suitable approach to both the micro (user) and the macro (processes) scale. Hence, a single infrastructure can support both the logistic and monitoring issues related to the war against a pandemic. Based on the COVID-19 experience, this paper is a survey on how state-of-the-art RFID systems can be employed in facing future pandemic outbreaks. The three pillars of the contrast of the pandemic are addressed: 1) use of Personal Protective Equipment (PPE), 2) access control and social distancing, and 3) early detection of symptoms. For each class, the envisaged RFID devices and procedures are discussed based on the available technology and the current worldwide research. This survey shows that RFID could generate an extraordinary amount of data so that complementary paradigms of Edge Computing and Artificial intelligence can be tightly integrated to extract profiles and identify anomalous events in compliance with privacy and security.

Accelerated ripening through the exposure of fruits to controlled environmental conditions and gases is nowadays one of the most assessed food technologies, especially for climacteric and exotic products. However, a fine granularity control of the process and consequently of the quality of the goods is still missing, so the management of the ripening rooms is mainly based on qualitative estimations only. Following the modern paradigms of Industry 4.0, this contribution proposes a non-destructive RFID-based system for the automatic evaluation of the live ripening of avocados. The system, coupled with a properly trained automatic classification algorithm based on Support Vector Machines (SVMs), can discriminate the stage of ripening with an accuracy greater than 85%.

Recently introduced self-tuning RFID tags are capable to dynamically modify the input impedance of the embedded microchip transponder in order to compensate possible impedance mismatch with the antenna, thus making the communication performance rather insensitive to the nearby environment. A general method for the design of this new class of tags is presented with the purpose to master the complex configuration, where the tag is placed at a close distance from the interrogating antenna and the free-space assumption is not valid. A two-port system is introduced and the networkoriented reformulation of self-tuning action permits to derive an optimization problem for the minimization of the interrogation power for a wide range of boundary conditions. The method is demonstrated, both numerically and experimentally, through the application of a Finger Augmentation Device aimed to achieve a smart interaction with touched objects.