Flood Monitoring System


Flooding is an increasing problem faced by urban areas due to increasing unpredicted rainfall and climate changes. As IoT technology advances, it now has become possible to monitor rivers, coast and lake to observe the rate of water escalation. By mainly using Wireless System Networks (WSNs) and Machine to Machine (M2M) technology, sensor nodes are deployed in strategic and prone locations of flood along the watershed in which these sensors transmit water level and water flow data to a local base station. The base station, in return, retransmits the data to the data processing centre. The designed software processes the data into spatial distribution of flood risk for each controlled watershed. Finally, the computed risks can be used to give alerting messages to related government agencies or communities (El-Bendary et al., 2013).

Critical analysis of flood monitoring system

IoT implementation in flood monitoring indeed will drive changes in the infrastructure systems and services. Previously, the responsible agencies observe the water escalation manually, but now they have to prepare the system (the management, operator, software, and hardware) (Flood Network, 2017).

Technically in IoT implementation, they have to define the controlled watershed in the city and choose the most prone flood areas then they also have to prepare the hardware installation in the field. The hardware has to be able to obtain the data needed which can be sent successfully to the base station. Simultaneously, the software must be operated properly to manage the raw data into meaningful data. Furthermore, the system will receive a big data continuously in which adequate hardware and proper data analysis are needed. The obtained data can be used as feeds to the other system (e.g GIS), input for mapping or early warning system to the communities. Regarding urban planning, the data acts as valid and precise data to guide urban planners to exclude development in areas prone to flooding and make anticipation strategies.

Regarding economic implications, IoT creates more possibilities for technology providers and allows private or government agencies to collaborate together. The capital cost of IoT deployment is expensive as it requires hardware and software installations to make public and private partnership possible to happen. However, before proceeding with steps above, government agencies and municipalities have to set public policies and regulations to support the IoT implementation. One of it is mechanism is to allow private sector participation and access of the data for communities, taking into account data security.

As this system needs advanced technology, and government and communities’ readiness, the system is more likely to be implemented in the urban cities that are developed. In order to increase community understanding, government can set marketing program by providing information about the IoT and its advantages to the communities and the cities.

Regarding improvement, in the future, the technology will be further developed. Factors than can be improved are: less energy usage of the hardware, cost effective prevention through the generation of selected meaningful data, exploration of the potentiality of the flood map.

This technology has been implemented in Oxford, United Kingdom. The data is collected from the sensors in the database by wireless systems. The sensor is over hanged above water and by ultrasound technology, it detects water surface in an interval of 15 minutes (Flood Network, 2017). These main principle can be seen in Figure 2. Furthermore, the data can be accessed by communities in real time through a website (Figure 3).


Figure 1. Main principle of flood monitoring system in Oxford, United Kingdom (Flood Network, 2017)


Figure 2. Visualization of real time flood monitoring system in Oxford, United Kingdom (Flood Network, 2017)

Stakeholders and responsible authorities

The stakeholders and responsible authorities are government agencies related to urban planning and environmental monitoring as well as the municipalities, private companies and communities. Government agencies and municipalities have to set public policies and regulations to support the IoT implementation. Government can have partnership with private companies regarding investment and installation. The final data might be distributed to the communities as early warning system. To implement the system successfully, government agencies and municipalities have to increase communities’ understanding by providing adequate information.

SWOT analysis

Flood monitoring system using IoT has positive and negative ways. Some of them are explored in a SWOT analysis below (Table 1).

Table 1. SWOT Analysis of flood monitoring system



  • Give us real time information, predictive models, and early warning systems (El-Bendary et al., 2013)
  • Decrease the monitoring cost and gain efficient coverage of the monitored watershed (Ancona et al., 2015)
  • Better water management in the city
  • Their main limits are high power consumption, inadequate communication mechanisms and costs (Ancona et al., 2015)
  • New technology so people need time to adapt to the system



  • Use an M2M network with minimal power requirements (Ancona et al., 2015)
  • Use the data for future urban planning
  • E-waste (waste of electrical and electronic equipment)
  • Government and community readiness to use the technology



El-Bendary, N., Mostafa, M., Ramadan, R., Banerjee, S. and Hassanien, E. (2013). Smart Environmental Monitoring Using Wireless Sensor Networks. 1st ed. Cairo: Cairo University, p.750.

Flood Network. (2017). Flood Network. [online] Available at: https://flood.network/ [Accessed 1 Mar. 2017].


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