A Mote Interface for Fiber Optic Spectral Sensing With Real-Time Monitoring of the Marine Environment

O’Connell, Eoin; Healy, Michael; O'Keeffe, Sinéad; Newe, Thomas; Lewis, Elfed

doi:10.1109/jsen.2013.2258760

Cited by 10 publications

(6 citation statements)

References 15 publications

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“…We will also look at the benefits that real-time monitoring offers, such as the capacity to quickly respond to deviations from ideal conditions, the creation of predictive models, remote accessibility, and the sending of timely notifications in the case of urgent events. By [6] the end of this thorough investigation, it will be clear that real-time water quality monitoring in aquaculture using IoT sensors and cloud-based analytics is more than a technological advancement; it is a game-changer for an industry that is at the forefront of addressing global food security challenges while ensuring environmental sustainability. We will reveal this innovation's transformational potential as we explore the nuances of it, as well as its power to usher in a new era of excellence in aquaculture.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Water Quality Monitoring in Aquaculture using IoT Sensors and Cloud-Based Analytics

Stojanovic,

Chaudhary

2023

RJCSE

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The health and productivity of aquatic creatures in aquaculture systems depend on maintaining ideal water quality conditions. The production of seafood worldwide is significantly influenced by aquaculture. Conventional monitoring techniques can entail lengthy processes, are rare, and lack the promptness necessary to prevent and alleviate unfavourable circumstances. This study proposes a novel method for monitoring water quality in real time in aquaculture, utilising cloud-based analytics and Internet of Things (IoT) sensors. Within aquaculture facilities, strategically positioned Internet of Things (IoT) sensors continuously collect information on key water quality factors, such as water and air temperature, light intensity, humidity, pH levels, wind speed, and ammonia nitrogen content. A cloud-based analytics platform receives real-time data from these sensors, processes it using cutting-edge algorithms, and then analyses the data. This holistic approach offers a variety of advantages. Real-time monitoring enables aquaculturists to quickly spot deviations from ideal conditions, lowering the danger of disease outbreaks and aquatic species mortality. To optimise farming practises and resource allocation, historical data gathered in the cloud is used to build predictive models. Aquaculturists may monitor and manage their systems remotely, which improves operational efficiency and lessens the need for on-site staff. This is a major benefit. The system can also send warnings and alarms in the event of anomalous circumstances, ensuring quick reactions to urgent situations.

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Section: Introductionmentioning

confidence: 99%

Real-Time Water Quality Monitoring in Aquaculture using IoT Sensors and Cloud-Based Analytics

Stojanovic,

Chaudhary

2023

RJCSE

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“…WSNs consist of sensor nodes that are distributed throughout the process industry area. These sensor nodes sense, process, and communicate data to the base station [2]. WSN has been effectively implemented in home automation, monitoring of environmental conditions, remote patient monitoring, and so on [3].…”

Section: Introductionmentioning

confidence: 99%

Maximization of length and lifetime of clustered industrial automation network

2017

Teh. vjesn.

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Original scientific paperThe main function of industrial automation networks (IANs) is to monitor and control processes. In general, the sensor nodes utilize batteries as an energy source to control processes. The clustered IAN aims at maximizing the lifetime of the sensor node by improving the energy efficiency. The proposed system is targeted for utilization of the long distance wireless transmission radio modules where the energy distribution needs to be reduced to a greater extent. This paper presents the impact of adopting sleeping mechanisms in transmitting a physical variable from the industrial area to the base station where the controller is present. The number of transmissions that occurs due to the application of aggressive sleeping behaviour has been compared to the normal sleeping behavioural approach. The energy spent by the network for communication greatly depends on the number of transmissions. Hence, the network lifetime can be maximized by minimizing the energy spent for transmission. Keywords: energy efficiency; industrial automation; routers; sensors; WSN; ZigBee Maksimizacija duljine i trajanja klasterirane mreže industrijske automatizacijeIzvorni znanstveni članak Osnovna funkcija mreža industrijske automatizacije -IANs (Industrial Automation Networks) je nadzor i upravljanje procesima. Općenito, čvorovi senzora koriste baterije kao izvor energije za upravljanje procesima. Svrha je klasteriranog IAN-a maksimiziranje vijeka trajanja senzorskog čvora poboljšanjem energetske učinkovitosti. Predloženi je sustav namijenjen primjeni radio modula s bežičnim prijenosom na daljinu gdje se razvođenje energije treba znatno smanjiti. U radu se daje prikaz djelovanja primjene prikrivenih (spavajućih) mehanizama u prijenosu fizičke varijable iz industrujskog područja u baznu stanicu gdje postoji regulator. Broj prijenosa zbog primjene agresivnog prikrivenog ponašanja uspoređen je s pristupom uobičajenom prikrivenom ponašanju (sleeping behavioral approach). Energija koju troši komunikacijska mreža uvelike ovisi o broju prijenosa. Prema tome se vijek trajanja mreže može maksimalno produžiti minimiziranjem energije potrošene za prijenos.

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“…To date, although there have been some reports of the integration of optical sensors into a WSN platform e.g. by O'Connell et al [3], most WSN systems do not use optical fibre sensors and thus fail to benefit from the synergy of both technologies -accessing the advantages seen in the use of a wireless sensor networks and at the same time coupling these to the benefits of the advanced design and the significant capabilities of optical fibre sensors. In addition, mobile robots have been used widely to perform a wide range of critical tasks such as exploration, search and rescue operations, and reconnaissance [4].…”

Section: Introductionmentioning

confidence: 99%

A Novel Wireless Mobile Platform to Locate and Gather Data From Optical Fiber SensorsIntegrated Into a WSN

et al. 2015

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract-This paper presents a novel design for a wireless mobile platform to locate and gather data from different types of optical fiber sensors, thereby enabling the more effective integration of a number of such optical fiber sensors with an advanced mobile wireless sensor network (WSN). This then more readily permits potential applications, such as monitoring in remote and harsh environments and tracking, exploiting fully the combined advantages offered both by the mobile WSN and the advanced optical fiber sensing technologies. The platform which was designed and implemented consists of an optical fiber sensor module and a smart mobile WSN module, which shows important advantages for mobile sensing and tracking and mesh networking. In this paper, a fiber Bragg gratingbased temperature sensor and an intrinsic pH optical fiber sensor were specially designed and integrated successfully into the optical fiber sensor module as an exemplar to investigate the performance of the integrated system based on the mobile WSN platform. The positive experimental results obtained have confirmed the functionality of the platform designed and demonstrated its capacity for real-time optical fiber sensor data monitoring, processing, and wireless transmission. The successful creation of this type of wireless mobile platform with optical fiber sensors can thus be expected to make an important impact on a number of sectors, where either conventional optical sensor designs or WSNs alone cannot meet the systems requirements. Permanent repository link

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A Mote Interface for Fiber Optic Spectral Sensing With Real-Time Monitoring of the Marine Environment

Cited by 10 publications

References 15 publications

Real-Time Water Quality Monitoring in Aquaculture using IoT Sensors and Cloud-Based Analytics

Real-Time Water Quality Monitoring in Aquaculture using IoT Sensors and Cloud-Based Analytics

Maximization of length and lifetime of clustered industrial automation network

A Novel Wireless Mobile Platform to Locate and Gather Data From Optical Fiber SensorsIntegrated Into a WSN

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