Dhruval Singh, Govind Sharma, Ishan Minhas, Gurkirat Singh, P. Mahajan, P. Verma, Gitanjali Chandwani Manocha
{"title":"LoRaWAN Gateway Architecture for Aquaculture Monitoring in Rural Area","authors":"Dhruval Singh, Govind Sharma, Ishan Minhas, Gurkirat Singh, P. Mahajan, P. Verma, Gitanjali Chandwani Manocha","doi":"10.1109/ISCON57294.2023.10111936","DOIUrl":null,"url":null,"abstract":"In fish farming, it is imperative to have detailed data about water quality, dissolved oxygen and nutrients etc., not only in large scale classic farming applications but also for urban aquaculture. To ensure the survival of the fish, the water should be monitoring at regular intervals. This periodic monitoring is cumbersome and prone to human error if done manually. Live and automated monitoring will not only save human effort but also increase the productivity of the fishing farming. This automated monitoring requires robust network connectivity to ensure live data collection using sensors and storage in cloud/server. However, for rural area the network connectivity may or may not be available. LoRaWAN is very popular Internet of Things (IoT) access network technology. In this paper, we carry out experiment to extend the network range using LoRaWAN (Long Range Wide Area Network) for live and automated aquaculture monitoring. The monitoring is done with the various sensors that collect data related to quality of water at different time and sending the data to the nearest LoRaWAN Sensor Node, which further forwards the aggregated data to LoRaWAN gateway. The LoRaWAN radio module that allows long-range wireless data transmission and low-power battery operation for several months at reasonable module costs The proposed system is evaluated in terms of transmission range, battery runtime and sensor data accuracy.","PeriodicalId":280183,"journal":{"name":"2023 6th International Conference on Information Systems and Computer Networks (ISCON)","volume":"362 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 6th International Conference on Information Systems and Computer Networks (ISCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCON57294.2023.10111936","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In fish farming, it is imperative to have detailed data about water quality, dissolved oxygen and nutrients etc., not only in large scale classic farming applications but also for urban aquaculture. To ensure the survival of the fish, the water should be monitoring at regular intervals. This periodic monitoring is cumbersome and prone to human error if done manually. Live and automated monitoring will not only save human effort but also increase the productivity of the fishing farming. This automated monitoring requires robust network connectivity to ensure live data collection using sensors and storage in cloud/server. However, for rural area the network connectivity may or may not be available. LoRaWAN is very popular Internet of Things (IoT) access network technology. In this paper, we carry out experiment to extend the network range using LoRaWAN (Long Range Wide Area Network) for live and automated aquaculture monitoring. The monitoring is done with the various sensors that collect data related to quality of water at different time and sending the data to the nearest LoRaWAN Sensor Node, which further forwards the aggregated data to LoRaWAN gateway. The LoRaWAN radio module that allows long-range wireless data transmission and low-power battery operation for several months at reasonable module costs The proposed system is evaluated in terms of transmission range, battery runtime and sensor data accuracy.
在鱼类养殖中,无论是在大规模的传统养殖应用中,还是在城市水产养殖中,都需要详细的水质、溶解氧和营养成分等数据。为确保鱼的存活,应定期监测水质。如果手动进行这种定期监视,将会很麻烦,而且容易出现人为错误。实时和自动化监控不仅可以节省人力,还可以提高渔业生产效率。这种自动化监控需要强大的网络连接,以确保使用传感器和存储在云/服务器中的实时数据收集。然而,对于农村地区,网络连接可能可用,也可能不可用。LoRaWAN是非常流行的物联网(IoT)接入网技术。本文利用LoRaWAN (Long range Wide Area network,远程广域网)扩展网络范围,开展水产养殖现场自动化监测实验。监测是通过各种传感器完成的,这些传感器在不同的时间收集与水质有关的数据,并将数据发送到最近的LoRaWAN传感器节点,该节点进一步将聚合的数据转发到LoRaWAN网关。LoRaWAN无线电模块允许远程无线数据传输和低功耗电池运行数月,模块成本合理。该系统在传输范围、电池运行时间和传感器数据精度方面进行了评估。