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An IoT-based system for monitoring and forecasting flash floods in real-time

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Abstract

Floods are the most frequent of all natural disasters that occur in India. Although one of the main reasons for these disasters is the variations in monsoon and heavy inflows during the four months of the rainy season, India's asymmetric geomorphic features play an important role in determining the nature and intensity of floods in different regions. The destruction due to floods can be monitored with Internet of Things (IoT) systems. Flood forecasting can be done to warn people and evacuate them to safer places. A real-time end-to-end system generates an early flood alert based on various hydro-meteorological parameters received from sensing devices. In this study, an IoT-based system senses the hydrological data such as water discharge and water level, as well as data related to climate like rainfall, humidity, temperature, wind direction and speed. The task of estimating the water discharge gets difficult since rivers have changing geographic properties. To resolve this issue, a novel technique is proposed to estimate river discharge based on the sectional area and flow of the river. Additionally, the challenges associated with quantifying the overall quantity of rainfall resulting from the unpredictable behaviour of the local meteorological conditions have been addressed.

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References

  • Abdullahi S I, Habaebi M H and Malik N A 2019a Intelligent flood disaster warning on the fly: developing IoT-based management platform and using 2-class neural network to predict flood status; Bull. Electrical Eng. Inform. 8(2) 706–717.

    Article  Google Scholar 

  • Abdullahi S I, Habaebi M H and Malik N A 2019b Capacitive electrode sensor implanted on a printed circuit board designed for continuous water level measurement; Bull. Electrical Eng. Inform. 8(2) 450–459.

    Article  Google Scholar 

  • Al Qundus J, Dabbour K, Gupta S, Meissonier A and Paschke A 2020 Wireless sensor network for AI-based flood disaster detection; Ann. Oper. Res., pp. 1–23.

  • Arduino 2023 UNO R3. 2023(23-Feb-2023).

  • Barcelo-Ordinas J M, Doudou M and Garcia-Vidal J 2019 Self-calibration methods for uncontrolled environments in sensor networks: a reference survey; Ad Hoc Networks 88 142–159.

    Article  Google Scholar 

  • Basnyat B, Singh N and Roy N 2020 Design and deployment of a flash flood monitoring IoT: Challenges and opportunities; 2020 IEEE International Conference on Smart Computing (SMARTCOMP), pp. 422–427.

  • Bisht S, Chaudhry S and Sharma S 2018 Assessment of flash flood vulnerability zonation through Geospatial technique in high altitude Himalayan watershed, Himachal Pradesh India; Rem. Sens. Appl.: Soc. Environ. 12 35–47.

    Google Scholar 

  • Bruschi P, Piotto M and Dell’Agnello F 2016 Wind speed and direction detection by means of solid-state anemometers embedded on small quadcopters; Proc. Eng. 168 802–805.

    Article  Google Scholar 

  • Camuffo D, Becherini F and della Valle A 2022 How the rain-gauge threshold affects the precipitation frequency and amount; Clim. Change 170(1–2) 7.

    Article  Google Scholar 

  • Dragulinescu A M, Dragulinescu A and Zamfirescu C 2019 Smart Neighbourhood: LoRa-based environmental monitoring and emergency management collaborative IoT platform; 2019 22nd International Symposium on Wireless Personal Multimedia Communications (WPMC), pp. 1–6.

  • Earl B 2023 Calibrating Sensors, https://cdn-learn.adafruit.com/downloads/pdf/calibrating-sensors.pdf.

  • Fadhilah U and Pratama R 2022 Comparison study of measurement results between rain gauge 7052.0100 and optical rain gauge 815 at Lapan Kototabang; Pillar of Phys. 15(1).

  • Furquim G, Filho G P R, Jalali R, Pessin G, Pazzi R W and Ueyama J 2018 How to improve fault tolerance in disaster predictions: A case study about flash floods using IoT, ML and real data; Sensors 18(3) 907, https://doi.org/10.3390/s18030907.

    Article  Google Scholar 

  • Geisler T, Wolf M and Götzl G 2023 Optimizing the geothermal potential of tunnel water by separating colder sectional discharges – Case study Brenner Base Tunnel; Renew. Energ. 203 529–541.

    Article  Google Scholar 

  • Ghapar A A, Yussof S and Bakar A A 2018 Internet of things (IoT) architecture for flood data management; Int. J. Future Gener. Commun. Netw. 11(1) 55–62.

    Google Scholar 

  • Golombek N Y, Scheingross J S and Repasch M N 2021 Fluvial organic carbon composition regulated by seasonal variability in lowland river migration and water discharge; Geophys. Res. Lett. 48(24) e2021GL093416.

    Article  Google Scholar 

  • Han K, Zhang D, Bo J and Zhang Z 2012 Hydrological monitoring system design and implementation based on IoT; Phys. Proc. 33 449–454.

    Article  Google Scholar 

  • Hart J K and Martinez K 2015 Toward an environmental Internet of Things; Earth Space Sci. 2(5) 194–200.

    Article  Google Scholar 

  • Hassan W H W, Jidin A Z, Aziz S A C and Rahim N 2019 Flood disaster indicator of water level monitoring system; Int. J. Elec. Comput. Eng. (IJECE) 9(3) 1694.

    Article  Google Scholar 

  • Hu Y, Zhou J and Li J 2022 Tipping-bucket self-powered rain gauge based on triboelectric nanogenerators for rainfall measurement; Nano Energy 98 107234.

    Article  Google Scholar 

  • Jasni A A, Ahmad Y A and Gunawan T S 2022 Tributary water depth and velocity remote monitoring system using Arduino and LoRa; 2022 IEEE 8th International Conference on Computing, Engineering and Design (ICCED), pp. 1–6.

  • Jayashree S, Sarika S and Solai A L 2017 A novel approach for early flood warning using android and IoT; 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), pp. 339–343.

  • Khan W A, Das P and Ghosh S 2020 Smart IoT Communication: Circuits and Systems; 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS), pp. 699–701.

  • Khanna A and Kaur S 2020 Internet of things (IoT), applications and challenges: a comprehensive review; Wireless Personal Commun. 114 1687–1762.

    Article  Google Scholar 

  • Kitagami S, Thanh V T and Bac D H 2016 Proposal of a distributed cooperative IoT system for flood disaster prevention and its field trial evaluation; Int. J. Internet Things 5(1) 9–16.

    Google Scholar 

  • Koestoer R, Pancasaputra N and Roihan I 2019 A simple calibration methods of relative humidity sensor DHT22 for tropical climates based on Arduino data acquisition system; AIP Conf. Proc. 2062(1) 020009.

    Article  Google Scholar 

  • Lanza L G, Cauteruccio A and Stagnaro M 2022 Chapter 4 – Rain gauge measurements; In: Rainfall (ed.) Morbidelli R, Elsevier, pp. 77–108.

  • Lo S-W, Wu J-H, Lin F-P and Shu C-H 2015 Visual sensing for urban flood monitoring; Sensors 15(8) 20,006–20,029.

    Article  Google Scholar 

  • Mendoza-Cano O, Aquino-Santos R, López-de la Cruz J, Edwards R M, Khouakhi A, Pattison I, Rangel-Licea V, Castellanos-Berjan E, Martinez-Preciado M A, Rincón-Avalos P, Lepper P, Gutiérrez-Gómez A, Uribe-Ramos J M, Ibarreche J and Perez I 2021 Experiments of an IoT-based wireless sensor network for flood monitoring in Colima, Mexico; J. Hydroinfor. 23(3) 385–401.

    Article  Google Scholar 

  • Merkuryeva G, Merkuryev Y and Sokolov B V 2015 Advanced river flood monitoring, modelling and forecasting; J. Comput. Sci. 10 77–85.

    Article  Google Scholar 

  • Mitra P, Ray R, Chatterjee R, Basu R, Saha P, Raha S, Barman R, Patra S and Biswas S 2016 Flood forecasting using Internet of things and artificial neural networks; 2016 IEEE 7th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), Vancouver, BC, Canada, 2016, pp. 1–5, https://doi.org/10.1109/IEMCON.2016.7746363.

  • Mohanty M P, Mudgil S and Karmakar S 2020 Flood management in India: a focussed review on the current status and future challenges; Int. J. Disaster Risk Reduct. 49 101660.

    Article  Google Scholar 

  • Mousa M, Zhang X and Claudel C 2016 Flash flood detection in urban cities using ultrasonic and infrared sensors; IEEE Sens. J. 16(19) 7204–7216.

    Article  Google Scholar 

  • Nižetić S, Šolić P and López-de-Ipiña González-de-Artaza D 2020 Internet of things (IoT): opportunities, issues and challenges towards a smart and sustainable future; J. Clean. Prod. 274 122877.

    Article  Google Scholar 

  • Pierleoni P, Concetti R, Belli A and Palma L 2020 Amazon, Google and Microsoft Solutions for IoT: architectures and a performance comparison; IEEE Access 8 5455–5470.

    Article  Google Scholar 

  • Prafanto A and Budiman E 2018 A Water Level Detection: IoT Platform Based on Wireless Sensor Network; 2018 2nd East Indonesia Conference on Computer and Information Technology (EIConCIT), pp. 46–49.

  • Ro Y, Chang K H, Hwang H, Kim M, Cha J W and Lee C 2022 Comparative study of rainfall measurement by optical disdrometer, tipping-bucket rain gauge, and weighing precipitation gauge; Reasearh Square.

  • Sahoo A K and Udgata S K 2020 A novel ANN-based adaptive ultrasonic measurement system for accurate water level monitoring; IEEE Trans. Instr. Meas. 69(6) 3359–3369.

    Article  Google Scholar 

  • Satendra A K G, Naik V K, Roy T K S, Sharma A K and Dwivedi M 2015 Uttarakhand Disaster 2013; National Institute of Disaster Management, Ministry of Home Affairs, Govt. of India, New Delhi.

  • Schenato L, Aguilar-López J P and Galtarossa A 2021 A rugged FBG-based pressure sensor for water level monitoring in dikes; IEEE Sens. J. 21(12) 13,263–13,271.

    Article  Google Scholar 

  • Shah J and Mishra B 2020 IoT-enabled low power environment monitoring system for prediction of PM2.5; Pervasive Mob. Comput. 67 101175.

    Article  Google Scholar 

  • Shah W M, Arif F, Shahrin A and Hassan A 2018 The implementation of an IoT-based flood alert system; Int. J. Adv. Computer Sci. Appl. (IJACSA) 9(11).

  • Simmhan Y, Ravindra P, Chaturvedi S, Hegde M and Ballamajalu R 2018 Towards a data-driven IoT software architecture for smart city utilities; J. Softw.: Practice Exper. 48(7) 1390–1416.

    Google Scholar 

  • Sunkpho J and Ootamakorn C J S 2011 Real-time flood monitoring and warning system; Songklanakarin J. Sci. Technol. 33(2) 227–235.

    Google Scholar 

  • Tsao Y C, Kuo Y W and Wu C C 2022 Implementation and Design of Water Flow Meter of Smart Home Integrated with Environment Monitor System; 2022 IEEE 4th Eurasia Conference on Biomedical Engineering, Healthcare and Sustainability (ECBIOS), pp. 126–131.

  • Ullo S L and Sinha G R 2020 Advances in smart environment monitoring systems using IoT and sensors; Sensors (Basel) 20(11) 3113.

    Article  Google Scholar 

  • Vogt M 2018 Radar Sensors (24 and 80 GHz Range) for Level Measurement in Industrial Processes; 2018 IEEE MTT-S Int. Conf. Microwaves for Intelligent Mobility (ICMIM), pp. 1–4.

  • Yuliandoko H, Subono S, Wardhani V A, Pramono S H and Suwindarto P 2018 Design of flood warning system based IoT and water characteristics; TELKOMNIKA Telecom., Comput., Electron. Control 16(5) 2101–2110.

    Google Scholar 

  • Zhang M and Li X 2020 Drone-enabled internet-of-things relay for environmental monitoring in remote areas without public networks; IEEE Internet of Things J. 7(8) 7648–7662.

    Article  Google Scholar 

  • Zhou L, Wu X and Xu Z 2018 Emergency decision making for natural disasters: an overview; Int. J. Disaster Risk Reduct. 27 567–576.

    Article  Google Scholar 

Download references

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Authors and Affiliations

Authors

Contributions

CP: Acquiring geographic information, analytical modelling, result evaluation and analysis, and writing the original paper. AB: Collecting field data, analytical modelling, result evaluation and analysis. DA: Conceptual design of the task, monitoring of data collection and analytical modelling, review of the manuscript, and general assistance.

Corresponding author

Correspondence to Anurag Barthwal.

Additional information

Communicated by Parthasarathi Mukhopadhyay

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Prakash, C., Barthwal, A. & Acharya, D. An IoT-based system for monitoring and forecasting flash floods in real-time. J Earth Syst Sci 132, 159 (2023). https://doi.org/10.1007/s12040-023-02172-4

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  • DOI: https://doi.org/10.1007/s12040-023-02172-4

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