Adaptive data synchronization algorithm for IoT-oriented low-power wide-area networks

The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications

Light-weight integration and interoperation of localization systems in IoT

As the ideas and technologies behind the Internet of Things (IoT) take root, a vast array of new possibilities and applications is emerging with the significantly increased number of devices connected to the Internet. Moreover, we are also witnessing the fast emergence of location-based services with an abundant number of localization technologies and solutions with varying capabilities and limitations. We believe that, at this moment in time, the successful integration of these two diverse technologies is mutually beneficial and even essential for both fields. IoT is one of the major fields that can benefit from localization services, and so, the integration of localization systems in the IoT ecosystem would enable numerous new IoT applications. Further, the use of standardized IoT architectures, interaction and information models will permit multiple localization systems to communicate and interoperate with each other in order to obtain better context information and resolve positioning errors or conflicts. Therefore, in this work, we investigate the semantic interoperation and integration of positioning systems in order to obtain the full potential of the localization ecosystem in the context of IoT. Additionally, we also validate the proposed design by means of an industrial case study, which targets fully-automated warehouses utilizing location-aware and interconnected IoT products and systems

A Low-Cost IoT Based Buildings Management System (BMS) Using Arduino Mega 2560 And Raspberry Pi 4 For Smart Monitoring and Automation

This work presents an internet of things (IoT) based building management system (BMS) for monitoring, control, and energy management in buildings to provide an efficient way of energy utilization. Existing systems mainly provide monitoring of different parameters with limited controlling/automation functions. Existing solutions also do not provide automatic decision-making, advanced safety management, and resource tracking. However, the proposed system provides a comprehensive way of monitoring, controlling, and automatic decision making regarding different environmental and electrical parameters in buildings, i.e., temperature, humidity, dust, volt, etc., by using a low-cost wireless sensor network (WSN). The architecture of the proposed system consists of five layers and uses analog sensors which are connected to Arduino Mega 2560 microcontrollers for data collecting, NodeMCUs ESP8266 for wireless communication, Raspberry Pi4 microcomputers for decision making, and nod-RED dashboard which runs locally on a Raspberry Pi 4to provide a friendly end-user interface. The system also uses the Message Queuing Telemetry Transport (MQTT) communication protocol through Wi-Fi and completely relies on the local devices in the architecture and does not need cloud computing services. The proposed system provides two different kinds of automation, i.e., safety automation for the safety of different devices with advanced features, and energy automation. The proposed system is also able to provide humidity control inside a room and to track and count the available resources in any facility. The proposed system is low cost, scalable, and can be used in any building. Simulation results show that the proposed system is highly efficient

Data center environment monitoring system

The Internet of things (IoT) is applied to many cases in the smart cities topic. We apply an IoT-developed platform using LoRa communication to a Data Center to understand temperature behavior within a concentration of servers and the working behavior of these server machines. We describe our work as an IoT platform to measure temperature, humidity, and energy consumption in these data centers. In the end, the gradient temperature was found in the rack, and the increasing temperature is correlated with energy consumption and the backup routines in the night. Our developed approach can be used to understand CPU usage and related temperature and the energy consumption.info:eu-repo/semantics/publishedVersio

A low-cost and do-it-yourself device for pumping monitoring in deep aquifers

Water crises due to climate change, high population growth and increasing demands from industry and agriculture claim for increasing efficiency and universalizing water resources management strategies and techniques. Water monitoring helps providing necessary evidences for making sound decisions about managing water resources both now and in the future. In this work, a low cost and “do it yourself” communication device is proposed to record water production and energy consumption of electric pumpings from deep boreholes/wells, and to predict the impact of the ongoing and previous pumpings in the evolution of the water level in the aquifer. The proposal incorporates an edge-computing approach for the simulation of the aquifer response in real-time. Computation of results of interest is performed at the sensor, minimizing communication requirements and ensuring almost immediate results. An approximated solution to physically based modeling of aquifer response is computed thanks to the a priori expression of the water level time evolution in a reduced basis. The accuracy is enough to detect deviations from expected behaviour. The energy consumption of the device is very much reduced with respect to that of a full modelling, which can be computed off-line for calibrating reduced model parameters and perform detailed analyses. The device is tested in a real scenario, in a mountain subbasin of the Ebro river in Spain, obtaining a good trade-off between performance, price, and energy consumption.This research has been partly supported by EU under grant agreement N. 825184 and funded by the Government of Spain under contracts PID2019-106774RB-C21, PID2019-106774RB-C22, and PID2020-113172RB-I00 and by the Government of Catalonia as Consolidated Research Groups 2017-SGR-688 and 2017-SGR-990, and Pre-consolidated Research Group 2017-SGR-1496. The APC was funded by the Open program from Universitat Rovira i Virgili.Peer ReviewedPostprint (published version