Elderly people with physical or cognitive disabilities such as visual impairment lack independence in their everyday activities, such as shopping in retail stores. Ambient assisted living (AAL) technologies can help. The authors of this article propose the use of RFID technologies to enable an AAL system in a retail store. This article presents an RFID-enabled intelligent system that can detect user-object interactions via a supervised machine learning algorithm. The authors' proposal detects RFID signals from different objects and classifies them as interacted or static objects through an automatic training system, achieving a detection accuracy over 86 percent.

IoT-based environments may infer anomalies based on the data processed from their heterogeneous sensors. Within the technologies evolving the IoT concept, nowadays the Radio Frequency Identification (RFID) technology is a de facto standard in areas like retail or logistics. For instance, most retailers attach RFID-labels to their items to avoid stock-out in the inventory or speed up cash processes. Besides identification, RFID provides further RF data which can be used for information management like anomaly detection (i.e. a shoplifting in a RFID loss prevention system). This manuscript presents two IoT scenarios to detect anomalies using multivariate outlier detection methods, uniquely using RFID data. This research empirically evaluates the authors' proposed methods by reproducing a RFID-enabled store, and the two proposed scenarios. The evaluation achieved a False Positive Rate around 0.1% and a True Positive Rate around 87%.

Global warming has increased uncertainty regarding managing traditional water supply systems. Unfortunately, there is a need for the smart management of water supply systems. This work aims to design a solution for renewing and securing critical infrastructure that supplies water and provides water purification inside the range of applications of Industry 4.0 for Smart Cities. Therefore, we analyze the renewal requirements and the applicable use cases and propose a solution based on IoT networks for critical infrastructure in the urban environment. We describe the architecture of the IoT network and the specific hardware for securing a water supply and wastewater treatment chain. In addition, the water level control process for the supply chain and the system that ensures the optimal level of chemicals for wastewater treatment are detailed. Finally, we present the guidelines for infrastructure operators to carry out this operation within Industry 4.0, constituting a development framework for future research on the design of Smart Cities.

Our society may enhance and create new services in a people-centric IoT context through the exchange of information with sensor devices. Unfortunately, communication and services may be compromised due to a number of factors including unreliable communication, complexity, and security threats like spoofing. Within the technologies involved in the IoT paradigm, passive RFID allows the inventorying of simple objects toward wireless communication with a low-cost investment. We present a solution to increase the personalization of IoT applications and services (e.g., accessing a restricted area with a contact- less card) by detecting people-object gestures with an accelerometer-enabled passive RFID tag. We demonstrate the feasibility of our proposal by achieving a precision of 85 percent in people-object gestures classification.