Slotted ALOHA Overlay on LoRaWAN: a Distributed Synchronization Approach

LoRaWAN is one of the most promising standards for IoT applications. Nevertheless, the high density of end-devices expected for each gateway, the absence of an effective synchronization scheme between gateway and end-devices, challenge the scalability of these networks. In this article, we propose to regulate the communication of LoRaWAN networks using a Slotted-ALOHA (S-ALOHA) instead of the classic ALOHA approach used by LoRa. The implementation is an overlay on top of the standard LoRaWAN; thus no modification in pre-existing LoRaWAN firmware and libraries is necessary. Our method is based on a novel distributed synchronization service that is suitable for low-cost IoT end-nodes. S-ALOHA supported by our synchronization service significantly improves the performance of traditional LoRaWAN networks regarding packet loss rate and network throughput.Comment: 4 pages, 8 figure

Ultra-low power IoT applications: from transducers to wireless protocols

This dissertation aims to explore Internet of Things (IoT) sensor nodes in various application scenarios with different design requirements. The research provides a comprehensive exploration of all the IoT layers composing an advanced device, from transducers to on-board processing, through low power hardware schemes and wireless protocols for wide area networks. Nowadays, spreading and massive utilization of wireless sensor nodes pushes research and industries to overcome the main limitations of such constrained devices, aiming to make them easily deployable at a lower cost. Significant challenges involve the battery lifetime that directly affects the device operativity and the wireless communication bandwidth. Factors that commonly contrast the system scalability and the energy per bit, as well as the maximum coverage. This thesis aims to serve as a reference and guideline document for future IoT projects, where results are structured following a conventional development pipeline. They usually consider communication standards and sensing as project requirements and low power operation as a necessity. A detailed overview of five leading IoT wireless protocols, together with custom solutions to overcome the throughput limitations and decrease the power consumption, are some of the topic discussed. Low power hardware engineering in multiple applications is also introduced, especially focusing on improving the trade-off between energy, functionality, and on-board processing capabilities. To enhance these features and to provide a bottom-top overview of an IoT sensor node, an innovative and low-cost transducer for structural health monitoring is presented. Lastly, the high-performance computing at the extreme edge of the IoT framework is addressed, with special attention to image processing algorithms running on state of the art RISC-V architecture. As a specific deployment scenario, an OpenCV-based stack, together with a convolutional neural network, is assessed on the octa-core PULP SoC

Embedding Temporal Convolutional Networks for Energy-efficient PPG-based Heart Rate Monitoring

Photoplethysmography (PPG) sensors allow for non-invasive and comfortable heart rate (HR) monitoring, suitable for compact wrist-worn devices. Unfortunately, motion artifacts (MAs) severely impact the monitoring accuracy, causing high variability in the skin-to-sensor interface. Several data fusion techniques have been introduced to cope with this problem, based on combining PPG signals with inertial sensor data. Until now, both commercial and reasearch solutions are computationally efficient but not very robust, or strongly dependent on hand-tuned parameters, which leads to poor generalization performance. In this work, we tackle these limitations by proposing a computationally lightweight yet robust deep learning-based approach for PPG-based HR estimation. Specifically, we derive a diverse set of Temporal Convolutional Networks for HR estimation, leveraging Neural Architecture Search. Moreover, we also introduce ActPPG, an adaptive algorithm that selects among multiple HR estimators depending on the amount of MAs, to improve energy efficiency. We validate our approaches on two benchmark datasets, achieving as low as 3.84 beats per minute of Mean Absolute Error on PPG-Dalia, which outperforms the previous state of the art. Moreover, we deploy our models on a low-power commercial microcontroller (STM32L4), obtaining a rich set of Pareto optimal solutions in the complexity vs. accuracy space

Performance Comparison between Decawave DW1000 and DW3000 in low-power double side ranging applications

Indoor localization and context-awareness are becoming two of the key technologies for a large variety of applications. Real-time locating systems with centimeter accuracy and low power consumption have recently been made available by employing the Ultra WideBand (UWB) technology. Since 2015, Decawave has produced commercial UWB integrated circuits, exploiting time-of-flight measurement techniques to estimate the distance between two agents. This work presents a performance study between two Decawave transceivers, the DW1000 and the new DW3000 released in 2020. The testing space includes areas under line-of-sight and diverse non-line-of-sight conditions caused by the reflection of the UWB radio signals across various obstacles. Finally, we analyze the power consumption in distinct configurations, comparing the two devices. Results show that the two have similar precision in measurement ranges above one meter, while the DW3000 performs, on average, 33.2% better considering shorter distances. Moreover, the new transceiver features reduced power consumption by almost 50% during real-time measurements reaching an average value of 55 mW

Slotted ALOHA Overlay on LoRaWAN: a Distributed Synchronization Approach

LoRaWAN is one of the most promising standards for IoT applications. Nevertheless, the high density of end-devices expected for each gateway, the absence of an effective synchronization scheme between gateway and end-devices, challenge the scalability of these networks. In this article, we propose to regulate the communication of LoRaWAN networks using a Slotted-ALOHA (S-ALOHA) instead of the classic ALOHA approach used by LoRa. The implementation is an overlay on top of the standard LoRaWAN; thus no modification in pre-existing LoRaWAN firmware and libraries is necessary. Our method is based on a novel distributed synchronization service that is suitable for low-cost IoT end-nodes. S-ALOHA supported by our synchronization service significantly improves the performance of traditional LoRaWAN networks regarding packet loss rate and network throughput

Poster Abstract: An Ultra-Low Power Wake up Radio with Addressing and Retransmission Capabilities for Advanced Energy Efficient MAC Protocols

Wireless sensor networks (WSNs) are today widely employed in real world applications. However, their lifetime is still challenging and the most critical limitation for the success of this technology. In fact, wireless sensors nodes, which are the backbone of the network, are typically powered by limited energy storage devices (i.e. small batteries or supercaps) and their short lifetime is a critical issue. To overcome this limitation a major research effort focuses on reducing power consumption, especially of communication, as the radio transceiver is one of the highest power consumers. A critical energy-efficiency issue in WSN transceivers is idle listening. Wake-up radio receivers are very effective in minimizing idle listening. This fact has resulted in a significant number of wake-up radio receiver architectures proposed in last decade. In this work we present an advanced design and implementation of an advanced wake-up radio that is capable of both processing the received data (i.e. for addressing) and retransmitting data or wake up messages to the neighbours when necessary. With these features it can be possible to further enhance the energy efficiency of the communication and allowing ultra-low power multi-hop communication. Experimental results demonstrate the functionality as well as the power and range of the proposed design which is ready for future energy efficient and pure-asynchronous MAC protocols

An experimental system to acquire aeroacoustic properties on wind turbine blades

Wind turbine noise is a key issue preventing the successful exploitation of the full potential of wind energy throughout the world, especially in urban areas. To better assess and predict wind turbine noise, several aeroacoustic simulations and models have been developed over the past. Many semi-empirical models for noise emission and propagation rely on aeroacoustic properties at the blade level, including the pressure gradient, the spectrum of the pressure fluctuations, the convection velocity and the coherence lengths. Field measurements of these local quantities on operating wind turbines are valuable to improve the accuracy of the models. In the Aerosense project, a cost-effective smart measurement system is being developed that is thin, easy to install without damaging the blade, low power, self-sustaining and wirelessly transmitting. This measurement system uses MEMS sensors, which require some calibrations and corrections to obtain sufficiently accurate data. This paper describes the experimental system and its workflow, which has been developed within the Aerosense project to obtain sufficiently accurate measurements for semi-empirical noise emission and propagation models. The experimental system and its workflow are then validated in an anechoic wind tunnel on a NACA63-418 airfoil. The results show that this experimental system is able to acquire relevant aeroacoustic properties on operating wind turbines.ISSN:1742-6588ISSN:1742-659

An accurate low-cost Crackmeter with LoRaWAN communication and energy harvesting capability

Structural health monitoring (SHM) systems are becoming increasingly widespread and are in some cases mandated by law. A major factor limiting the diffusion of such systems is the lack of low-cost low-power sensor nodes, which can be deployed in large numbers in hard-to-reach areas, while providing high-quality precise measurements over their entire lifespan with minimum maintenance and withstanding climatic stress. In this paper, we present a cost-effective wireless component for Structural Health Monitoring (SHM) that measure and track cracks in concrete and other construction materials. The sensor combines a microprocessor with LoRaWAN wireless communication, an analog transducer, and a solar energy harvester, allowing long-term remote monitoring with easy plug and play installation. Experimental results demonstrate that we achieved about 1\mu\mathrmm accuracy and an expected lifetime of more than 10 years, with stable measurements across a-IS-65\ub0C temperature range

A low cost, highly scalable wireless sensor network solution to achieve smart LED light control for green buildings

Reducing energy demand in the residential and industrial sectors is an important challenge worldwide. In particular, lights account for a great portion of total energy consumption, and unfortunately a huge amount of this energy is wasted. Light-emitting diode (LED) lights are being used to light offices, houses, industrial, or agricultural facilities more efficiently than traditional lights. Moreover, the light control systems are introduced to current markets, because the installed lighting systems are outdated and energy inefficient. However, due to high costs, installation issues, and difficulty of maintenance; existing light control systems are not successfully applied to home, office, and industrial buildings. This paper proposes a low cost, wireless, easy to install, adaptable, and smart LED lighting system to automatically adjust the light intensity to save energy and maintaining user satisfaction. The system combines motion sensors and light sensors in a low-power wireless solution using Zigbee communication. This paper presents the design and implementation of the proposed system in a real-world deployment. Characterization of a commercial LED panel was performed to evaluate the benefit of dimming for this light technology. Measurements of total power consumption over a continuous six months period (winter to summer) of a busy office were acquired to verify the performance and the power savings across several weather conditions scenarios. The proposed smart lighting system reduces total power consumption in the application scenario by 55% during a six month period and up to 69% in spring months. These figures take also into account individual user preferences

Slotted ALOHA on LoRaWAN-Design, Analysis, and Deployment

LoRaWAN is one of the most promising standards for long-range sensing applications. However, the high number of end devices expected in at-scale deployment, combined with the absence of an effective synchronization scheme, challenge the scalability of this standard. In this paper, we present an approach to increase network throughput through a Slotted-ALOHA overlay on LoRaWAN networks. To increase the single channel capacity, we propose to regulate the communication of LoRaWAN networks using a Slotted-ALOHA variant on the top of the Pure-ALOHA approach used by the standard; thus, no modification in pre-existing libraries is necessary. Our method is based on an innovative synchronization service that is suitable for low-cost wireless sensor nodes. We modelled the LoRaWAN channel with extensive measurement on hardware platforms, and we quantified the impact of tuning parameters on physical and medium access control layers, as well as the packet collision rate. Results show that Slotted-ALOHA supported by our synchronization service significantly improves the performance of traditional LoRaWAN networks regarding packet loss rate and network throughput