In this paper, we propose FlexTDOA, an indoor localization method and a system using ultra-wideband (UWB) radios. Our method uses time-difference of arrival (TDOA) localization so that the user device remains passive and is able to compute its location simply by listening to the communication between the fixed anchors, ensuring the scalability of our system. The anchors communicate using a custom-designed, flexible time-division multiple-access (TDMA) scheme in which time is divided in slots, and in each slot one anchor interrogates one or more anchors which respond in the same slot. Clock synchronization between the anchors is not needed. We implemented FlexTDOA on in-house designed hardware using a commercial UWB module. We compare FlexTDOA against the classic TDOA approach and range-based localization in a deployment of ten anchors and one tag, both with and without obstructions. Results show that FlexTDOA achieves the highest localization accuracy in most of the scenarios. We also evaluate the localization accuracy under multiple conditions by varying parameters such as the number of responses, their order, and the number of anchors. We simulate and evaluate the effect of the physical speed of the tag on the choice of optimum system parameters.

Internet of Things (IoT) systems deployments are becoming both ubiquitous and business critical in numerous business verticals, both for process automation and data-driven decision-making based on distributed sensors networks. Beneath the simplicity offered by these solutions, we usually find complex, multi-layer architectures—from hardware sensors up to data analytics systems. These rely heavily on software running on the on-location gateway devices designed to bridge the communication between the sensors and the cloud. This will generally require updates and improvements—raising deployment and maintenance challenges. Especially for large scale commercial solutions, a secure and fail-safe updating system becomes crucial for a successful IoT deployment. This paper explores the specific challenges for infrastructures dedicated to remote application deployment and management, addresses the management challenges related to IoT sensors systems, and proposes a mathematical model and a methodology for tackling this. To test the model’s efficiency, we implemented it as a software infrastructure system for complete commercial IoT products. As proof, we present the deployment of 100 smart soda dispensing machines in three locations. Each machine relies on sensors monitoring its status and on gateways controlling its behaviour, each receiving 133 different remote software updates through our solution. In addition, 80% of the machines ran non-interrupted for 250 days, with 20% failing due to external factors; out of the 80%, 30% experienced temporary update failures due to reduced hardware capabilities and the system successfully performed automatic rollback of the system, thus recovering in 100% of the temporary failures.

This paper documents the change and reproduction of gender status in the motion picture industry by discussing patterns in protagonist choice and authorship of biographical films produced from 1900 to 2017. The results rely on a quantitative analysis of all 4,539 films on the IMDb platform labeled with the “Biography” tag that portray an individual main character in the selected years. We find that men-only filmmaking teams have been remarkably consistent from 1900 onward in their choice of male subjects, while mixed and women-only teams have driven an increase in the central representation of women as figures whose life is worthy of narration and remembrance. Therefore, the recently increased involvement of women as directors has significantly advanced the symbolic recognition of women in public cinematographic discourse. Our findings document the emergence of a transitional period in the biographical movie industry in which the reproduction of gender status asymmetries coexists with an increased participation of women in filmmaking.

High voltage power line inspection is a critical task that can be automated by using UAV (Unmanned Aerial Vehicle) inspection. Automated navigating along power lines remains however an open challenge, with current available sensors systems limited in terms of accuracy and consistency by environmental variables. The current work presents an automated power line detection system based on the magnetic signature from an active power line. This paper will discuss the design, testing and fine tuning of a magnetic field sensor system optimized to measure the distance and relative bearing of the power line.

Considering the widespread presence of switching devices on the power grid (including renewable energy system inverters), network distortion is more prominent. To maximize network efficiency, our goal is to minimize these distortions. Measuring the voltage and current total harmonic distortion (THD) using power meters and other specific equipment, and assessing power factor and peak currents, represents a crucial step in creating an efficient and stable smart grid. In this paper, we propose a power meter capable for measuring both standard electrical parameters and power quality parameters such as the voltage and current total harmonic distortion factors. The resulting device is compact and DIN-rail-mountable, occupying only three modules in an electrical cabinet. It integrates both wired and wireless communication interfaces and multiple communication protocols, such as Modbus RTU/TCP and MQTT. A microSD card can be used to store the device configuration parameters and to record the measured values in case of network fault events, the device’s continuous operation being ensured by the integrated backup battery in this situations. The device was calibrated and tested against three industrial power meters: Siemens SENTRON PAC4200, Janitza UMG-96RM, and Phoenix Contact EEM-MA400, obtaining an overall average measurement error of only 1.22%.