Localizing objects in indoor environments with anchor-based systems poses several challenges to be faced. The main one is the design phase. What is the minimum number of anchors to be adopted? What is the optimal placement of the anchors in the operating domain? These are typical issues that need to be solved in this stage. Such issue is generally addressed by several experimental tests, imposing high costs both in the required large amounts of time and in the use of devices. In addition, sometimes the experiments will not warrant to identify the optimal design solution. In this work, a black-box design tool is proposed, able to manage different environments, in terms of domain size, maximum number of available anchors, device metrological features, and target performance. Such an approach, to be effective, needs a preliminary validation versus experimental results to make the future performance predictions reliable and avoid unexpected localization accuracy degradation. For this reason, the presented work adopts a side-by-side development, by evaluating results’ compatibility, in static and dynamic contexts, before addressing further and more complex analyses relying on the design tool only. Such a comparison proves the goodness of the developed design tool, and the outcomes allow an accurate localization system design by finding anchors’ placement solutions with the minimum computational burden.

Nowadays, low-power wireless technologies like Wi-Fi, ZigBee, Bluetooth, to cite a few, are often present in measurement environment. Sometimes, they can be considered as unwanted disturbances. Many times, they are used as communication medium to realize smart data transmission. Among them, Wi-Fi is the most widespread in the development of wireless local area networks (WLANs), and because of its good data transmission rates and plug-and-play capabilities, it is the main candidate for integrating measurement instruments in wireless networks. Although designed and developed to reduce at minimum its radiated emissions, Wi-Fi has to be considered as a potential interfering source for modern instrumentation that often has bandwidth and operating frequencies including the Wi-Fi band. For these reasons, a careful investigation on the electromagnetic susceptibility of measurement systems, when subjected to Wi-Fi, is carried out in this paper. Disturbance effects due to the Wi-Fi technology on typical measurement stations, including spectrum analyzers, digital oscilloscopes, universal counters, and digital multimeters, are analyzed. The achieved results prove that the effects of interferences due to the wireless module on modern instrumentation are often not negligible, thus potentially compromising its metrological performance and the measurement result reliability.

Cyber security is one of the most crucial aspects of the Internet of Things (IoT). Among the possible threats, great interest is today paid toward the possible capturing of information caused by external attacks on both client and server sides. Whatever the IoT application, the involved nodes are exposed to cyberattacks mainly through the vulnerability of either the sensor nodes themselves (if they have the capabilities for networking operativity) or the IoT gateways, which are the devices able to create the link between the local nodes of the IoT network, and the wide area networks. Due to the low-cost constraints typical of many IoT applications, the IoT sensor nodes and IoT gateways are often developed on low-performance processing units, in many cases customized for the specific application, and thus not easy to update against new cyber threats that are continuously identified. In the framework of cyberattacks aimed at capturing sensitive information, one of the most known was the heartbleed, which, has allowed attackers to remotely read protected memory from an estimated 24–55 percent of popular HTTPS sites. To overcome such a problem, which was due to a bug of the OpenSSL, a suitable patch was quickly released, thus allowing to avoid the problem in most of the cases. However, IoT devices may require more advanced mitigation techniques, because they are sometimes unable to be patched for several practical reasons. In this scenario, the paper proposes a novel measurement method for inline detecting intrusions due to heartbleed and heartbleed-like attacks. The proposed solution is based on an effective rule which does not require decoding the payload and that can be implemented on a low-performance general-purpose processing unit. Therefore, it can be straightforwardly implemented and included in either IoT sensor nodes or IoT gateways. The realized system has been tested and validated on a number of experiments carried out on a real network, showing performance comparable (in some cases better) with the heavier machine learning-based methods.

This paper deals with the electromagnetic susceptibility of measurement systems when subjected to interference generated by short-range, low-power wireless transmitters. A ZigBee transmitter was used as an interfering source operating close to the instrumentation under test. The results of numerous tests prove that different kinds of measurement instrumentation can be affected by the wireless module interference. Significant metro- logical performance decay was observed for both frequency- and time-domain measurements carried out by instrumentation whose bandwidth includes the ZigBee frequency operating range.