Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring

Xu, Zhaozhuo; Pu, Fangling; Fang, Xin; Fu, Jing

doi:10.1155/2016/4178079

Cited by 16 publications

(6 citation statements)

References 31 publications

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“…RPi B+ model also contains 802.11ac wireless LAN card that is used for wireless communication (e.g., wireless ad hoc connection). It is also deployed as an intelligent sensor node [43,44,46] in many WSN networks and boosted by a micro SD card.…”

Section: Experimental Setup and Resultsmentioning

confidence: 99%

Proposition and Real-Time Implementation of an Energy-Aware Routing Protocol for a Software Defined Wireless Sensor Network

Younus

Islam²,

Kim

2019

Sensors

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A wireless sensor network (WSN) has achieved significant importance in tracking different physical or environmental conditions using wireless sensor nodes. Such types of networks are used in various applications including smart cities, smart building, military target tracking and surveillance, natural disaster relief, and smart homes. However, the limited power capacity of sensor nodes is considered a major issue that hampers the performance of a WSN. A plethora of research has been conducted to reduce the energy consumption of sensor nodes in traditional WSN, however the limited functional capability of such networks is the main constraint in designing sophisticated and dynamic solutions. Given this, software defined networking (SDN) has revolutionized traditional networks by providing a programmable and flexible framework. Therefore, SDN concepts can be utilized in designing energy-efficient WSN solutions. In this paper, we exploit SDN capabilities to conserve energy consumption in a traditional WSN. To achieve this, an energy-aware multihop routing protocol (named EASDN) is proposed for software defined wireless sensor network (SDWSN). The proposed protocol is evaluated in a real environment. For this purpose, a test bed is developed using Raspberry Pi. The experimental results show that the proposed algorithm exhibits promising results in terms of network lifetime, average energy consumption, the packet delivery ratio, and average delay in comparison to an existing energy efficient routing protocol for SDWSN and a traditional source routing algorithm.

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Section: Experimental Setup and Resultsmentioning

confidence: 99%

Proposition and Real-Time Implementation of an Energy-Aware Routing Protocol for a Software Defined Wireless Sensor Network

Younus

Islam²,

Kim

2019

Sensors

View full text Add to dashboard Cite

show abstract

“…For instance, machine learning applications within a vehicle [8], at face detection and tracking [9], and in botany [10]. Other similar works taking advantage of Raspberry Pis have also been explored [11][12][13][14][15][16][17].…”

Section: Related Workmentioning

confidence: 99%

Deploying a Task-based Runtime System on Raspberry Pi Clusters

Gupta,

Brandt,

Wagle

et al. 2020

Preprint

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Arm ® technology is becoming increasingly important in HPC. Recently, Fugaku, an Arm ® -based system, was awarded the number one place in the Top500 list. Raspberry Pis provide an inexpensive platform to become familiar with this architecture. However, Pis can also be useful on their own. Here we describe our efforts to configure and benchmark the use of a Raspberry Pi cluster with the HPX/Phylanx platform (normally intended for use with HPC applications) and document the lessons we learned. First, we highlight the required changes in the configuration of the Pi to gain performance. Second, we explore how limited memory bandwidth limits the use of all cores in our shared memory benchmarks. Third, we evaluate whether low network bandwidth affects distributed performance. Fourth, we discuss the power consumption and the resulting trade-off in cost of operation and performance.

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“…The configuration of those systems has been facilitated with the adoption of flexible open-source hardware platforms, such as Raspberry Pi and Arduino, a recent trend that influenced CityAlarm. In [20], the authors proposed a rainfall emergency notification solution to alert people to critical situations, using the Raspberry Pi platform to detect them. Besides sensing the rain level, the created nodes can perform predictions about upcoming heavy rain, which could be easily reconfigured or adapted for different scenarios.…”

Section: Related Workmentioning

confidence: 99%

A Distributed Multi-Tier Emergency Alerting System Exploiting Sensors-Based Event Detection to Support Smart City Applications

Costa

Vasques

Portugal

et al. 2019

Sensors

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The development of efficient sensing technologies and the maturation of the Internet of Things (IoT) paradigm and related protocols have considerably fostered the expansion of sensor-based monitoring applications. A great number of those applications has been developed to monitor a set of information for better perception of the environment, with some of them being dedicated to identifying emergency situations. Current IoT-based emergency systems have limitations when considering the broader scope of smart cities, exploiting one or just a few monitoring variables or even allocating high computational burden to regular sensor nodes. In this context, we propose a distributed multi-tier emergency alerting system built around a number of sensor-based event detection units, providing real-time georeferenced information about the occurrence of critical events, while taking as input a configurable number of different scalar sensors and GPS data. The proposed system could then be used to detect and to deliver emergency alarms, which are computed based on the detected events, the previously known risk level of the affected areas and temporal information. Doing so, modularized and flexible perceptions of critical events are provided, according to the particularities of each considered smart city scenario. Besides implementing the proposed system in open-source electronic platforms, we also created a real-time visualization application to dynamically display emergency alarms on a map, demonstrating a feasible and useful application of the system as a supporting service. Therefore, this innovative approach and its corresponding physical implementation can bring valuable results for smart cities, potentially supporting the development of adaptive IoT-based emergency-aware applications.

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Raspberry Pi Based Intelligent Wireless Sensor Node for Localized Torrential Rain Monitoring

Cited by 16 publications

References 31 publications

Proposition and Real-Time Implementation of an Energy-Aware Routing Protocol for a Software Defined Wireless Sensor Network

Proposition and Real-Time Implementation of an Energy-Aware Routing Protocol for a Software Defined Wireless Sensor Network

Deploying a Task-based Runtime System on Raspberry Pi Clusters

A Distributed Multi-Tier Emergency Alerting System Exploiting Sensors-Based Event Detection to Support Smart City Applications

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