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Modern organizations face numerous physical security threats, from fire hazards to more intricate concerns regarding surveillance and unauthorized personnel. Conventional standalone fire and intrusion detection solutions must be installed and maintained independently, which leads to high capital and operational costs. Nonetheless, due to recent developments in smart sensors, computer vision techniques, and wireless communication technologies, these solutions can be integrated in a modular and low-cost manner. This work introduces Integrated Physical Security System (IP2S), a multi-agent system capable of coordinating diverse Internet of Things (IoT) sensors and actuators for an efficient mitigation of multiple physical security events. The proposed system was tested in a live case study that combined fire and intrusion detection in an industrial shop floor environment with four different sectors, two surveillance cameras, and a firefighting robot. The experimental results demonstrate that the integration of several events in a single automated system can be advantageous for the security of smart buildings, reducing false alarms and delays. [ABSTRACT FROM AUTHOR]

Energy sufficiency to build the world through the industrial revolution 4.0 has become a hot topic of research on energy since the last decade. Various researchers from all over the world have been competing in how to produce alternative electricity as an additional option from conventional power plants with the smallest investment figures. The specific objective of this research is to create technology for energy management in off-grid hybrid-powered buildings so that investment in hybrid electricity systems is optimal. The smart power outlet used ACS-712 current sensor and a ZMPT101B voltage sensor to measure the electricity. Arduino Nano microcontroller and ESP8266 NodeMCU made the device monitorable through the internet. Added a relay module to switch the device remotely. Also, there were micro SD module and DS3231 RTC to log the data. This device used the smartphone interface with the Android operating system. The smart power outlet experiment result was good, the average error was 3.27% with one data shift in the data logging between the delivery time and the timer in a 30 seconds gap. [ABSTRACT FROM AUTHOR]

Roll forming is a highly productive manufacturing process for complex profiles or precision tubes used in automotive, aerospace, building and many other industries. Shorter product life-cycles and increasing product customization require new manufacturing concepts. Digitalization enables companies to cope with these new challenges. Digitized machines and processes become one of the key factors in advanced roll forming. The application of smart sensors is a first step towards digitized roll forming. Edge devices enable the connection of different types of sensors in order to form smart objects which in turn can be assembled into smart factories. The better quality of collected smart data allows, for instance, the development of new roll forming applications and more detailed FE roll forming simulations. Higher flexibility in roll forming production and smaller lot sizes require new and fast methods for choosing the right roll forming line and setting it up. This paper presents a new model, based on FE-simulations without friction, for prediction of torques in roll forming lines, supporting the selection of roll forming lines or machine parameters. A semi analytic model is derived to predict the required driving torques of the rolls for different machine configurations without performing additional time consuming FE-simulations. The model is verified with data acquired by smart sensors installed in a 3D roll forming line. First results of this approach are presented and show the possibilities of the digital twin concept. [ABSTRACT FROM AUTHOR]