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Internet of Things (IoT)

Short overview​

General Description​

As described in KfW Remote Management, Monitoring, & Verification (RMMV) Guidebook for International Financial Cooperation, “A sensor is a device that monitors changes by converting signals (input) continuously and automatically from analog objects into a digital interface (output). Technological developments have empowered sensor connectivity through cloud/remote access, forming a global infrastructure of physical and virtual, internet-connected objects called the Internet of Things (IoT). A smart sensor measures and combines signal conditioning and signal processing within one device. For example: a SmartMeter signal processing within one device monitors electric energy consumption in (near) real-time, communicates with a central system or smart grid, and shares usage data with consumers and providers for billing, data analytics, customer targeting, and rate recommendations. Similarly, a Smart Water Meter provides high- resolution readings demand forecasting, scarcity ­prevention and leak notification.”

Potential for Climate Change Adaptation​

IoT is often applied in the context of industry and smart city development, transportation, smart energy management in buildings or management of power networks, agriculture, waste management, or health care (Nižetić et al. 2020). Either of them is prone to climate impacts and would benefit from climate change adaptation measures. That includes use of smart meters for reducing energy consumption in buildings or guiding urban traffic, among others. IoT applications can help to understand regional climate and climate change, as the data collected can be used to support climate change impact assessment as a basis for informed adaptation decisions (Salam 2024).

Potential for Disaster Risk Management​

IoT can support all along the DRM cycle, either before the disaster by increasing accuracy of forecast, or during the disaster by providing real time data and increasing communication among emergency responders. Overall, during the preparedness phase, IoT aids in monitoring and analysis. In the recovery phase, it assists by collecting environmental data (such as weather, chemicals, movement, and buildings), health data (including information on rescuers and stranded individuals), and position data to support rescue efforts (for those trapped, rescuers, and their vehicles) (Zeng et al. 2023).

Application in different Climate Hazards​

Flooding​

IoT solutions can increase accuracy of floods forecasts by using sensors such as rain gauges (rainfall), radar level sensors, ultrasonic sensors and force-sensitive resistors (water level), drifter and river drones (river flow velocity and water temperature), cameras (flood detection). Equally, IoT can be integrated into flood warning systems by estimating water discharge (Ghanbari et al. 2024).

Sea Level Rise​

IoT can deliver quantitative data on water parameters essential for monitoring sea level rise impacts and assessing the adaptation measures. Sea level rise increases tidal floods, shoreline erosion, saltwater intrusion, threatening for instance critical infrastructures such as water supply. IoT employs a lot of sensors to detect a lot of water parameters such as PH, temperature, dissolved oxygen, conductivity, changes in ground water levels, but also coastal wave height, period and direction (Girau et al. 2020).

Landslide​

To detect landslides, sensors such as “inertial sensors, accelerometers, bar extensometers, borehole inclinometers, rainfall sensors (e.g., rain gauge), and displacement meters” can be used (Zeng et al. 2023).

Water Scarcity / Drought​

IoT and its variety of sensors can be used for drought forecast and monitoring and improve water management to combat water scarcity. UNEP DTU Partnership lists four options for cities to combat drought with IoT support: decrease water consumption, lessen the use of freshwater by encouraging alternative sources (e.g. reclaimed water), efficiently allocate water to areas of greatest need, and secure additional water sources and storage facilities (UNEP DTU Partnership 2021).

Strong Winds / Storms​

IoT can be used to increase accuracy of storms, cyclones and hurricanes forecast, for instance using cameras and image processing algorithms (Zeng et al. 2023).

Forest / Bush Fires​

IoT can support the early detection of fire. For data collection, a system can for instance rely on both WSN in the forest, satellite network, and UAV that collect real time images (data collection layer). WSN sends data to the gateway that sends it to the ThingSpeak IoT cloud that aggregates and analyses the data (Sharma et al. 2020).

Extreme Temperatures​

IoT can support the detection of extreme temperatures. For instance, a quality management system was applied to the smart Seoul data of things to gather additional data to be used by urban meteorological information services to forecast heat and cold waves at the urban area scale (Park and Baek 2023).

Saltwater Penetration​

Thanks to its various sensors, IoT enables real time monitoring of saltwater penetration (Nishan et al. 2024), in particular for critical infrastructures affected by salt intrusion such as pipelines and reservoirs. It can also assist in evaluating the effectiveness of measures designed to adapt to salt penetration.

Application in DRM / CCA Measures​

Nature-based Solutions​

IoT can be used to create urban forest and biosphere maps, balance green and built-in spaces, and vegetation cover monitoring and management (Belli et al. 2020). It can also be used to manage green spaces in cities. For instance, the city of London used IoT sensors in parks to monitor the moisture level and adapt watering accordingly, which resulted in the reduction of water consumption of 30% (Mourisard 2023).

Integrated Coastal Zone Protection​

IoT can be used to monitor coastal erosion by putting sensors along the coastline or other determinants of coastal erosion, but also to support decision making on how to manage coastal area. IoT have been used to monitor ocean, water quality, coral reef, marine fish farm, wave and current monitoring, as well as beach monitoring and crowd detection (Girau et al. 2020).

Stormwater Management​

IoT can facilitate remote, real-time monitoring of water consumption, water levels and channel flows, allowing for use optimization, quality or management (Mourisard 2023). IoT can enhance monitoring by efficiently tracking rainfall, tank levels, water quality, and the status of valves and pumps (Okoli & Kabaso 2024; Alshami et al. 2024). This monitoring could allow more efficient rain water forecasting, harvesting and management. For instance, in Singapore, authorities have deployed an IoT-based real-time rainfall data collection system to predict flooding and improve water resource management (Mourisard 2023). It can enhance water conservation by capturing it and storing water more efficiently or optimising its use (Singh & Ahmed 2021). Sensors can sort water during collection, distinguishing between water suitable for household tasks or toilets and water that can be treated for drinking and cooking (Bhuyan and Yasmin 2022).

Waste Management​

IoT can support more efficient waste management and recycling, including the shift towards a circular economy (Nižetić et al. 2020). Several applications are currently used, from smart monitoring of waste bins, e.g. by bin filling level detection, waste temperature and fire detection, bin vibration occurrence and bin tilt, presence of waste operators, waste humidity, bin GPS location, to the smart coordination of waste trucks and the reduction of food waste (Nižetić et al. 2020). IoT can also be used to detect illegal dump sites and track hazardous waste (Belli et al. 2020).

Relevance within the Project Cycle​

IoT can be helpful throughout all phases of project implementation.

Project Preparation:

Developing the most beneficial project design can benefit hugely from available IoT data, for example on availability and usage of water or other resources, water flows, wind speeds, people movements or other or behavioural patterns.

Project Implementation:

IoT data can support measuring hazard impacts to inform project design. The same IoT devices can be used for monitoring project implementation. Sensors and cameras can replace or add to site visits for monitoring, and collect data in areas that are not accessible. Data can come from IoT already available or from IoT devices implemented as parts of the project itself.

Verification and Project Progress:

IoT can facilitate remote, real-time monitoring of progress made and project impacts. They can be particularly useful in areas that are difficult to access to close crucial data gaps.

Final Project Review:

Data from IoT devices can be valuable sources for project review, if they have been installed early enough to allow for constant monitoring.

Ex-Post Evaluation:

Data collected via IoT throughout the project can be used for evaluation purposes.

Technology Requirements​

To implement IoT, several technical and human components need to be in place (after Sikder et al. 2018):

  • Sensing layer to collect data: physical objects called sensors or devices such as cameras, smartphones, etc. (collect data) and actuators (carry out data)
  • Network layer to transfer the collected data to other devices of the same network. Diverse communication technologies are used in IoT devices such as Wi-Fi, Bluetooth, Zigbee, Z-Wave, LoRa, cellular network, etc. Networks can have different topologies (such as MESH, STAR, BUS, RING).
  • Data processing layer to process collected and transferred data, and sometimes to store it too. Often, a combination of fog computing and cloud computing allows for more efficient data analysis (Zeng et al. 2023).
  • Application layer to implement and present the results of the data processing”. For instance, smart mobility, healthcare, etc.
  • When technical innovations such as IoT are introduced in the workplace, it can create fear, pressure or stress at individual level. This can be worked on through the creation of a support unit, planning an appropriate testing and adoption phase and the creation of an incentive infrastructure (Hartwein et al. 2022). All these elements may vary depending on the phase of the disaster risk management cycle and the type of hazard. For example, the sensing layer may need to be fire or water resistant (Zeng et al. 2023).

Data protection: Smart meters provide insights into the con- sumption patterns of private households and are thus sensitive in terms of data privacy. Data transmission is only permitted for the applications required for utility industry operations. The use of personal data for other purposes will, depending on the applicable law, require consent from consumers RMMV Guidebook Section 2.3.1.

In addition, data security requirements also arise from national data protection regulations, which stipulate basic security requirements to protect the collected personal data, such as consumption, address, and names. Entities may be required under those rules to ensure the ongoing confidentiality, integrity, availability, and resilience of processing systems and services (technical and organizational measures). They need to ensure that the IT security measures are adequate to withstand attacks from hackers or cyber warfare directed at critical infra-structure (see RMMV Guidebook Section 2.3.2).

See also Sensors / SmartMeters (Internet of Things)

Summary Assessment​

Overall Effectiveness​

IoT offers potential for enhancing urban resilience by facilitating real-time monitoring, efficient resource management, and adaptive disaster risk reduction strategies. IoT can increase the accuracy of risk assessment and hazard forecasting, providing more data for decision-making. Real-time data also enhances community preparedness and minimizes damage since it allows for a quick response. This capacity to anticipate, detect, and respond to risks strengthens the resilience of urban systems against climate-related hazards.

Moreover, IoT fosters effective post-disaster recovery and long-term urban planning by collecting and analyzing comprehensive data on damage and vulnerabilities. During recovery phases, IoT assists rescue operations by tracking health and location data of both responders and victims, improving operational efficiency.

Overall Efficiency​

IoT demonstrates versatility and can be used in very different context and to address different risks. Although the implementation of IoT requires substancial resources in terms of devices and infrastructure, the cost of operation might be deduced with savings that result from its application. IoT facilitates smarter resource management by collecting and analysing data on resource consumption and conditions, which leads to lower maintenance costs.

As the price of IoT devices has become more acceptable (Nižetić et al. 2020), IoT is also relatively affordable. It can have low energy usage and is able to operate in challenging environments, and is also relatively easy to install (Zeng et al. 2023).

Key Challenges and Limitations​

Environmental costs: While IoT can optimise energy and natural resources uses, it needs substantial energy to collect, aggregate and analyse the data. Increased use of IoT technologies leads to intense utilisation of fossil technologies (Nižetić et al. 2020). This could also put a strain on electric grids. The increasing use of IoT devices is also problematic as about 20% of electronic waste is recycled, and electronic equipment relies on limited metals and resources that are often extracted with various chemicals, water and fossil fuels impacting the environment (Nižetić et al. 2020).

Social costs: By reducing the need for labour and limiting direct social interactions, IoT technologies could have important social impacts (Nižetić et al. 2020).

Privacy, cybersecurity, and trust issues are of huge importance to consider as most of the technological safeguards developed to mitigate them have proven ineffective “and are likely to continue to fail due to inherent flaws” (Bibri et al. 2023).

Specifically, in regard to smart cities, the main challenges for implementation can be listed as follow: “efficient integration of different sensing technologies, development of a suitable network infrastructure, education of population, investigation of the sustainability aspect, such as carbon footprint, etc” (Nižetić et al. 2020).

Finally, technology may fail in crucial moments. For example, in the response phase some communication networks may be interrupted (Zeng et al. 2023). For more comprehensive information on these challenges and limitations, see the Principles for Digital Development, the Global Digital Compact, as well as Mejias and Couldry (2024).

Recommendations to optimize the Use of the Digital Tool​

Policymakers and developers should prioritize sustainable design by incorporating energy-efficient sensors and renewable energy sources into IoT infrastructure to minimize the carbon footprint of IoT networks. Moreover, initiatives to improve electronic waste management, such as incentivizing recycling and adopting circular economy principles for IoT device manufacturing, can reduce the environmental degradation caused by the production of new devices.

The implementation of IoT should focus on fostering inclusivity and trust. Public education campaigns can demystify IoT technologies, encouraging community engagement and participation in urban resilience initiatives. This promotes a higher acceptance of new systems and opens the possibility of creating solutions that are more adequate for different groups and communities. By promoting transparency in IoT data collection and usage, cities can build trust among citizens and reduce resistance to adoption.

In order to identify and mitigate technology-related human rights risks within KfW-financed projects, we recommend to use the KfW Human Rights Check for Financial Development Cooperation during project preparation and implementation.

Project Examples / Use Cases​

  • Colombia's National Unit for Disaster Risk Management manages an early warning system using IoT. Solar-powered sensors monitor water levels and air temperature using ultrasound (sensor layer) and send it through a 900MHz mesh network with Xbeee protocol (network layer), since the area was not well covered with 3G , to the Raspberry Pi 3B in the village control centre. Data is processed and sent to the eagle.io system software to store the data on the cloud (data processing layer), to Twilio to be visualised and stored in the cloud and send automatic messages to the village authorities when a risk is detected (application layer) (Libelium 2021).
  • The Busan Eco-delta Smart City is a master plan created with experts and civil participation in 2018. This plan aims at harmonising the major technologies of the 4th industrial revolution and the ecological settlements. It focuses on 10 areas to enhance quality of life through smart-city solutions, such as zero-energy city, smart health care, or smart water. The plan also includes a citizen engagement component. It can provide services with “quality and quantity of water, as well as drought and flood information” (Sangyoung Park 2020). The provision of real-time information to the public on water quality and quantity facilitates leakage detection and encourage the drinking from tap water (UNEP DTU Partnership 2021).

Linkages to other Tool Types​

  • Artificial Intelligence (AI): The Internet of Things (IoT) functions as data sources for AI algorithms. With wide coverage, IoT enables comprehensive urban planning powered by AI. Additionally, AI also shapes the IoT landscape, especially through the Artificial Intelligence of Things (AIoT), a more recent class of interconnected devices. In the AIoT, an AI algorithm makes decisions on multiple devices based on the information gathered.
  • Data sources: Given IoT’s data collection nature, it can consistently cover specific areas and domains in a controlled fashion. When integrated with Big Data for storage, processing and accessibility, it can be made available as input for other technologies. Additionally, like other data collection tools, the data generated by IoT can be made public as Open Data.
  • Digital Twins: IoT sensors, such as. RFID and laser scanners, collect real-time data of the physical environment. They can provide a constant flow of information to digital twins, enabling an accurate representation of the physical urban system. See also Building Information Modelling.
  • Communication and Collaboration: IoT can serve as a device for registering information, generating alerts and notifications to be communicated to citizens. Communication can also be further enhanced through IoT data made public. See also Collaboration and E-learning tools
  • Earth Observation tools: Earth observation tools and the IoT can work as complementary data collection systems. IoT collects granular real-time events, while earth observation tools capture broader-scale data, although less frequently. Furthermore, IoT might be able to support model calibration whenever geospatial models are being trained. See also Geospatial tools and GIS
  • Mobile tools: Mobile tools can complement sensors by collecting real-time data. Together, these technologies enable the collection and integration of data into urban analytical models for deeper analysis. See also Crowdsourcing Tools
  • (Remote) Management Information Systems (MIS): The integration of IoT wireless sensors, including cameras and drones, can provide near-real-time data to MIS, which can be used for not only planning but also monitoring interventions. See also Management Maintenance Systems (MMS) and (Remote) Management Information Systems

Licence​

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