IoT, Volume 1, Issue 1 (September 2020) – 9 articles

In this age of electronic communication, checking the physical mailbox is still part of our daily life. Mailboxes are placed several meters away from the house, and sometimes across the opposite side of a street. It is annoying to walk to the mailbox each day and realize that the mailbox is empty. In this paper, an Internet of Things (IoT)-connected smart mailbox is developed that automatically sends a notification to the smartphone whenever new mail arrives. This notification removes the frustration of an unnecessary trip to the mailbox. The proposed mailbox contains a low power device comprising of sensors, a system-on-chip microcontroller with Bluetooth Low Energy (BLE), and a rechargeable battery that charges with a solar panel. Whenever the mailbox door is closed, it checks the presence of mail and then sends the data to a hub using BLE. The hub is placed inside the house and sends a push notification to the smartphone using the home Wi-Fi. A smart speaker, Google Home, is also interfaced with the system, which can verbally say the status of the mailbox when asked a customized question. A prototype of the smart mailbox, the hub, and the smartphone app is developed and tested successfully. Full article

Chipless radio frequency identification (RFID) is a wireless technology that has the potential for many industrial applications, including the internet of things (IoT) applications, in which identification, sensing, and tracking are required. This technology has been improved during the last century. However, the processing of the backscattered signal in a chipless RFID system is still a challenge because the encoded data are embedded in the backscattered signal of a passive tag. The reader hardware, antennas, and the wireless channel have their own response in the received signal, which contains the tag ID information. The tag also produces a response, which is a combination of responses from different resonators, substrate, and copper reflection in a tag. In this paper, the reflection from a typical chipless RFID tag is analyzed, and all components of the backscattered signal are separated in both time and frequency domains. In addition, an equivalent circuit model for a backscattered chipless RFID tag is proposed, and the model is verified based on the actual performance of the resonator. This study has some important implications for future research. Full article

Smart meters have become a core part of the Internet of Things, and its sensory network is increasing globally. For example, in the UK there are over 15 million smart meters operating across homes and businesses. One of the main advantages of the smart meter installation is the link to a reduction in carbon emissions. Research shows that, when provided with accurate and real-time energy usage readings, consumers are more likely to turn off unneeded appliances and change other behavioural patterns around the home (e.g., lighting, thermostat adjustments). In addition, the smart meter rollout results in a lessening in the number of vehicle callouts for the collection of consumption readings from analogue meters and a general promotion of renewable sources of energy supply. Capturing and mining the data from this fully maintained (and highly accurate) sensing network, provides a wealth of information for utility companies and data scientists to promote applications that can further support a reduction in energy usage. This research focuses on modelling trends in domestic energy consumption using density-based classifiers. The technique estimates the volume of outliers (e.g., high periods of anomalous energy consumption) within a social class grouping. To achieve this, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Ordering Points to Identify the Clustering Structure (OPTICS) and Local Outlier Factor (LOF) demonstrate the detection of unusual energy consumption within naturally occurring groups with similar characteristics. Using DBSCAN and OPTICS, 53 and 208 outliers were detected respectively; with 218 using LOF, on a dataset comprised of 1,058,534 readings from 1026 homes. Full article

The Internet of Things (IoT) represents the binder of two worlds, specifically the real one and the digital one: tangible objects become recognizable in the virtual world, having digital matches, thus creating a network that enables the connection in-between the components. With the contemporary evolution of this domain, interconnectivity has become a primary fraction of new research and development directions. The Industrial Internet of Things (IIoT) is a concept that covers the more industrial level of the physical and digital connection and stays behind the Industry 4.0 concept. Supervisory control and data acquisition (SCADA) applications are important in the industry, their core being very present as complex products of big companies, at high prices. The Node-RED environment quickly evolved as one of the most important perspectives in IIoT, able to replace, up to a certain level, classic SCADA applications, bringing benefits to the industry. In this paper, the main focus is to evidence this aspect and to develop an application that will demonstrate the functionality of the concept, making use of protocols such as Modbus TCP (Transmission Control Protocol) for interacting with industrial devices and Message Queuing Telemetry Transport (MQTT) to interact with higher-levels, which provides a publish-subscribe structuring and a low band-width usage. The application uses logging and archiving modules based on InfluxDB database and is conceived to achieve the visual supervisory structure as close as possible to well-known SCADA solutions. The presented work results prove the efficiency of the solution. Full article

Industry 4.0 and digital farming rely on modern communication and computation technologies such as the Internet of Things (IoT) to provide smart manufacturing and farming systems. Having in mind a scenario with a high number of heterogeneous connected devices, with varying technologies and characteristics, the deployment of Industry 4.0 and digital farming solutions faces innovative challenges in different domains (e.g., communications, security, quality of service). Concepts such as network slicing and Software-Defined Networking (SDN) provide the means for faster, simpler, scalable and flexible solutions in order to serve a wide range of applications with different Quality-of-Service (QoS) requirements. Hence, this paper proposes a lightweight slice-based QoS manager for non-3GPP IoT focusing on different use cases and their varying requirements and characteristics. Our focus in this work is on non-3GPP IoT unlicensed wireless technologies and not specifically the end-to-end network slice perspective as described in 5G standards. We implemented and evaluated different QoS models in distinct scenarios in a real experimental environment in order to illustrate the potential of the proposed solution. Full article

During the last few years, various Industrial Internet of Things (IIoT) applications have emerged with numerous network elements interconnected using wired and wireless communication technologies and equipped with strategically placed sensors and actuators. This paper justifies why non-terrestrial networks (NTNs) will bring the IIoT vision closer to reality by providing improved data acquisition and massive connectivity to sensor fields in large and remote areas. NTNs are engineered to utilize satellites, airships, and aircrafts, which can be employed to extend the radio coverage and provide remote monitoring and sensing services. Additionally, this paper describes indicative delay-tolerant massive IIoT and delay-sensitive mission-critical IIoT applications spanning a large number of vertical markets with diverse and stringent requirements. As the heterogeneous nature of NTNs and the complex and dynamic communications scenarios lead to uncertainty and a high degree of variability, conventional wireless communication technologies cannot sufficiently support ultra-reliable and low-latency communications (URLLC) and offer ubiquitous and uninterrupted interconnectivity. In this regard, this paper sheds light on the potential role of artificial intelligence (AI) techniques, including machine learning (ML) and deep learning (DL), in the provision of challenging NTN-based IIoT services and provides a thorough review of the relevant research works. By adding intelligence and facilitating the decision-making and prediction procedures, the NTNs can effectively adapt to their surrounding environment, thus enhancing the performance of various metrics with significantly lower complexity compared to typical optimization methods. Full article

Precision Agriculture (PA) is an ever-expanding field that takes modern technological advancements and applies it to farming practices to reduce waste and increase output. One advancement that can play a significant role in achieving precision agriculture is wireless technology, and specifically the Internet of Things (IoT) devices. Small, inch scale and low-cost devices can be used to monitor great agricultural areas. In this paper, a system for precision viticulture which uses IoT devices for real-time monitoring is proposed. The different components of the system are programmed properly and the interconnection between them is designed to minimize energy consumption. Wireless sensor nodes measure soil moisture and soil temperature in the field and transmit the information to a base station. If the conditions are optimal for a disease or pest to occur, a drone flies towards the area. When the drone is over the node, pictures are captured and then it returns to the base station for further processing. The feasibility of the system is examined through experimentation in a realistic scenario. Full article