Informe mensual d'articles publicats. Campus Baix Llobregat. Base de dades Scopus. Febrer 2019

Informe bibliomètric mensual Campus Baix Llobregat. Base de dades Scopus. Febrer 2019Postprint (author's final draft

Powering Sigfox nodes with harvested energy

Sigfox is one of the popular LPWAN technologies used in the Internet of Things. As in the case of many other wireless protocols, Sigfox nodes are mainly powered with batteries, which leads to important maintenance costs and slows down its acceptance. Enabling such systems to work on harvested energy will facilitate their use and acceptance. We designed and tested a Sigfox node that can be powered by a 1 cm2 solar cell, opening the door to further optimization in size and costs. Preliminary tests made at the window of one of our office show that one can transmit tens of message per day with that node

Informe mensual d'articles publicats. Campus Baix Llobregat. Base de dades Scopus. Febrer i març 2019

Informe bibliomètric mensual Campus Baix Llobregat. Base de dades Scopus. Febrer i març 2019Postprint (published version

Comparison of wireless data transmission protocols for residential water meter applications

This article provides a comparison of various wireless data transmission protocols, such as Wireless M-Bus, LoRaWAN, Sigfox, NB-IoT and a newly developed proprietary protocol, studying their performance in the application of battery-powered residential water meters. Key aspects of the comparison include energy consumption, which is analyzed through comparing unitary amount of charge required to conduct a single, bi-directional data transaction between the meter and base station, and maximum coupling loss which effectively defines the range and coverage in the system. For completeness, the study includes also a brief cost analysis and ends with a conclusion, stating when each of the particular standards should be favored

Comparison of wireless data transmission protocols for residential water meter applications

This article provides a comparison of various wireless data transmission protocols, such as Wireless M-Bus, LoRaWAN, Sigfox, NB-IoT and a newly developed proprietary protocol, studying their performance in the application of battery-powered residential water meters. Key aspects of the comparison include energy consumption, which is analyzed through comparing unitary amount of charge required to conduct a single, bi-directional data transaction between the meter and base station, and maximum coupling loss which effectively defines the range and coverage in the system. For completeness, the study includes also a brief cost analysis and ends with a conclusion, stating when each of the particular standards should be favored

A Comparative Analysis on IoT Communication Protocols for Future Internet Applications

With the emergence of 5G, the Internet of Things (IoT) will bring about the next industrial revolution in the name of Industry 4.0. The communication aspect of IoT devices is one of the most important factors in choosing the right device for the right usage. So far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. And most of them are wireless protocols due to the sheer number of device requirements for IoT. In this paper, we summarize the network architectures of some of the most popular IoT wireless communications protocols. We also present them side by side and provide a comparative analysis revolving around some key features, including power consumption, coverage, data rate, security, cost, and Quality of Service (QoS). This comparative study shows that LTE-based protocols like NB-IoT and LTE-M can offer better QoS and robustness, while the Industrial, Scientific, and Medical (ISM) Band based protocols like LoRa, Sigfox, and Z-wave claim their place in usage where lower power consumption and lesser device complexity are desired. Based on their respective strengths and weaknesses, the study also presents an application perspective of the suitability of each protocol in a certain type of scenario and addresses some open issues that need to be researched in the future. Thus, this study can assist in the decision making regarding choosing the most suitable protocol for a certain field

Reducing Operation Cost of LPWAN Roadside Sensors Using Cross Technology Communication

Low-Power Wide-Area Network (LPWAN) is an emerging communication standard for Internet of Things (IoT) that has strong potential to support connectivity of a large number of roadside sensors with an extremely long communication range. However, the high operation cost to manage such a large-scale roadside sensor network remains as a significant challenge. In this paper, we propose LOC-LPWAN, a novel optimization framework that is designed to reduce the operation cost using the cross technology communication (CTC). LOC-LPWAN allows roadside sensors to offload sensor data to passing vehicles that in turn forward the data to a LPWAN server using CTC aiming to reduce the data subscription cost. LOC-LPWAN finds the optimal communication schedule between sensors and vehicles to maximize the throughput given an available budget of the user. Furthermore, LOC-LPWAN optimizes the fairness among sensors by allowing sensors to transmit similar amounts of data and preventing certain sensors from dominating the opportunity for data transmissions. LOC-LPWAN also provides an option that allows all sensor to transmit data within a specific delay bound. Extensive numerical analysis performed with real-world taxi data consisting of 40 vehicles with 24-hour trajectories demonstrate that LOC-LPWAN improves the throughput by 72.6%, enhances the fairness by 65.7%, and reduces the delay by 28.8% compared with a greedy algorithm given the same budget

On the energy performance of iridium satellite IoT technology

Most Internet of Things (IoT) communication technologies rely on terrestrial network infrastructure. When such infrastructure is not available or does not provide sufficient coverage, satellite communication offers an alternative IoT connectivity solution. Satellite-enabled IoT devices are typically powered by a limited energy source. However, as of this writing, and to our best knowledge, the energy performance of satellite IoT technology has not been investigated. In this paper, we model and evaluate the energy performance of Iridium satellite technology for IoT devices. Our work is based on real hardware measurements. We provide average current consumption, device lifetime, and energy cost of data delivery results as a function of different parameters. Results show, among others, that an Iridium-enabled IoT device, running on a 2400 mAh battery and sending a 100-byte message every 100 min, may achieve a lifetime of 0.95 years. However, Iridium device energy performance decreases significantly with message rate.This work was supported in part by the Spanish Government through project PID2019- 106808RA-I00, AEI/FEDER, EU, and by Secretaria d’Universitats i Recerca del Departament d’Empresa i Coneixement de la Generalitat de Catalunya through project 2017 SGR 376.Postprint (published version

Wireless monitoring and arima stream analytics system for freshwater lobster farm

Majority of the population are directly or indirectly dependent on aquaculture. Recent development in technology has a great impact on aquaculture. Among the crustacean breeds in Malaysia, Cherax Quadricarinatus species or also known as freshwater lobster has become favourable for farmers to breed them. Water quality monitoring has become a problem to farmers as predictions on water quality were observed conventionally through experience. In this research integration of IoT with forecasting for the freshwater lobsters were developed to do predictions based on real-time data. This IoT system consist of variety of sensors such as Electrical Conductivity (EC), Total dissolved Solid (TDS), Dissolve Oxygen (DO), potential of Hydrogen (pH), temperature and humidity were integrated to Arduino for sensing and transmitting data as End Node Unit. To ensure the reliability of collected data, the sensors have been calibrated with reference to manufacturing datasheet which contribute to the total of 25,920 data collected from August 2020 until January 2021. Those data were transmitted wirelessly from End Node Unit (ENU) and received by gateway and this bundle of data were parallelly uploaded to Cayenne Cloud via MQ Telemetry Transport (MQTT) protocol and saved in database in server through Wi-Fi. The real-time data of ENU in Structured Query Language (SQL) was displayed on the website purposely for remote monitoring. The real-time data query from ENU is streamed through Structured Query Language (SQL) right into R Studio and Autoregressive Integrated Moving Average (ARIMA) predictions were done on the query table. 70% of this stream real-time data query were taken as training dataset meanwhile another 30% were taken as testing dataset. Auto.arima functions are applied in the streaming dataset from SQL as it automatically chooses ARIMA models based on the pattern of the dataset. ARIMA models in this thesis were set to predict 24 hours while updating the real-time and prediction graph were set to one hour which monitored through the developed website. Moreover, the changes of parameter level in lobster’s tank can be notified through SMS in order to help the farmers to do remote monitoring. For DO, ARIMA, Neural Network Autoregressive (NNetAR) and Naïve Bayes accuracy on average are almost similar, with accuracy obtained in the range of 95% to 99%. For pH, ARIMA prediction are in the range of 95 % to 100 % while Naïve Bayes prediction range 89 % to 95 % and NNetAR prediction range are between 85 % to 95 % while for EC, NNetAR and Naïve Bayes indicate that prediction error of these two models are inaccurate by range 10% to 15% compared to error by ARIMA which is below 5%. In conclusion, ARIMA analytics does provide accurate predictions for monitoring water quality in freshwater lobster farms. The efficiency of this system has been proven with a 92.8% mortality rate

Feasibility of wireless horse monitoring using a kinetic energy harvester model

To detect behavioral anomalies (disease/injuries), 24 h monitoring of horses each day is increasingly important. To this end, recent advances in machine learning have used accelerometer data to improve the efficiency of practice sessions and for early detection of health problems. However, current devices are limited in operational lifetime due to the need to manually replace batteries. To remedy this, we investigated the possibilities to power the wireless radio with a vibrational piezoelectric energy harvester at the leg (or in the hoof) of the horse, allowing perpetual monitoring devices. This paper reports the average power that can be delivered to the node by energy harvesting for four different natural gaits of the horse: stand, walking, trot and canter, based on an existing model for a velocity-damped resonant generator (VDRG). To this end, 33 accelerometer datasets were collected over 4.5 h from six horses during different activities. Based on these measurements, a vibrational energy harvester model was calculated that can provide up to 64.04 mu W during the energetic canter gait, taking an energy conversion rate of 60% into account. Most energy is provided during canter in the forward direction of the horse. The downwards direction is less suitable for power harvesting. Additionally, different wireless technologies are considered to realize perpetual wireless data sensing. During horse training sessions, BLE allows continues data transmissions (one packet every 0.04 s during canter), whereas IEEE 802.15.4 and UWB technologies are better suited for continuous horse monitoring during less energetic states due to their lower sleep current