Monitoring indoor environments in buildings can be a useful tool in improving infrastructure efficiency. Water losses are an important parameter that can be evaluated through consumption monitoring.

Therefore, designing and implementing smart buildings for water consumption monitoring includes both the necessary hardware and associated software. The main purpose of such a system is to provide the user with transparent and easy-to-use real-time data.

By installing smart water meters and analyzing the collected data, it has been possible to detect consumption patterns and quantify and locate water losses. Observing additional hours of consumption across different platforms is essential as it can change water consumption habits and patterns, reducing costs for users and the entire system.

By increasing distribution efficiency and maintaining resource sustainability, smart water distribution can be achieved, as shown in the report "IoT Approach Towards Smart Water Usage," signed by I. Andrica, A. Vrsalovic, T. Perkovic, and M. Aglic, from the University of Split, Croatia.

The "IoT Ecosystem"

In recent years, responsibility for water use has increased significantly, aiming to ensure sustainable management in urban areas. To manage water consumption, leakage control and demand meters are used to measure water consumption.

Water meters are usually manual meter reading (MMR) devices that require the end user to travel and read water consumption regularly, making water consumption reading quite costly and complex.

However, recent advances in communication technologies have allowed the expansion of the IoT ecosystem, with many connected devices exchanging sensor data. This has enabled the development of automatic meter reading (AMR), which allows real-time data communication.

These technologies include wide-area, low-power networks, GSM-GPRS, Wi-Fi, Zigbee, 3G, and 4G long-term evolution (LTE). To improve building performance and estimate adequate sustainability and improvement measures, it is essential to examine the water consumption pattern, which is often unavailable due to lack of measurements.

Importance of a smart system

Using a smart water monitoring system can reveal temporal patterns or how water consumption varies over time due to numerous influencing factors, as well as information about water consumption intensity and peak demand.

This type of measurement technology allows disseminating water consumption knowledge to reduce costs, increase awareness, and enhance transparency.

All recorded consumption data is sent to a computerized platform displaying real-time usage statistics to consumers. This way, they have insight into the amounts consumed at any given time.

Additionally, the system allows detecting losses in the distribution system and any interruptions that can be detected in case of a sudden change in water quantity.

Using such a system is beneficial for both the user and the water distributor. As consumers become more aware of their consumption through continuous monitoring, the distributor also gains insight into consumption quantities and trends, allowing them to track water consumption with automatic meter reading without hiring additional staff.

Advantages of automatic reading systems

Using an automatic reader eliminates, among other things, the possibility of incorrect scale reading or human error. All these form the basis for understanding water usage patterns and identifying system issues and solutions.

Therefore, for long-term sustainability and better customer service, it is necessary to identify inadequacy and improve the distribution system through the integration of new technologies, such as smart water monitoring systems and infrastructure investments.

The latest findings suggest that data collected from different types of water consumption events can provide insight into tap water usage, ultimately providing information about population adaptation to hygiene practices.

User involvement in buildings is crucial to modify unfavorable consumption patterns; therefore, the implementation of smart meters should aim for a long-term change in customer satisfaction. To improve user awareness, initial and periodic field reliability checks of the system are required.

Changing consumption habits

In this study, three smart water meters were installed in a university building with a high daily turnover of people. Each water meter measures water flow in a separate building block, i.e., the first water meter measures the total water flow, while the other two meters measure water flow in two building blocks.

These water meters are equipped with LoRaWAN radio technology transceivers that can transmit information from difficult electromagnetic environments (e.g., in a parking lot and under a metal plate) to a central system.

Information about water consumption, especially in publicly available locations or available in a wallet-like IoT application, can lead to changes in water consumption habits and patterns, resulting in reduced overall system operating costs. Contributions include:

- A new approach has been implemented to record consumption patterns and identify water loss locations, as well as to quantify leaks by integrating measured data signal processing,

- An IoT Wallet application has been introduced that stores and previews data from an arbitrary sensor device, allows users to set rules for alarms, and has the ability to integrate an arbitrary sensor based on LoRaWAN radio technology,

- An analysis software has been introduced that can trigger alarms based on predetermined water consumption analysis thresholds,

- An energy consumption analysis of available IoT radio technologies was performed and verified on-site with available infrastructures.

Radio technology testing

Testing the availability of LPWA radio technology in underground water meter scenarios Since implementing IoT communication infrastructure in Croatia is still early, it is necessary to verify the availability of LPWA technologies in certain positions, in addition to underground positions where smart meters should be checked. be installed.

It is important to note that the given locations are harsh in terms of radio signal propagation, i.e., wireless communications, and need to be tested line-of-sight before installation. The testing procedure starts with establishing the data acquisition configuration from various IoT radios and performance measurements line-of-sight.

To test the availability of the three IoT radios, an initial testing configuration was established, both on the software side and the hardware side. The hardware configuration includes three Arduinos equipped with three different IoT radios (NB-IoT, LoRa, Sigfox).

To check if certain radios transmit, the Software Defined Radio (SDR) tool was used to listen on the radio channel between the Arduino radio and a specific receiver.

The same system can be used to determine signal power attenuation at a specific location, with the lid closed and open, providing better information about real-world radio data performance and physical limiting factors.

Experiment results

To obtain the experiment results with the visualization offered, for testing purposes, the LoRaWAN gateway was placed in the university building, while Sigfox and NBIoT clients rely on commercial infrastructure providers. The tests showed that the only reasonable technological approach among those tested is LoRa, i.e., LoRaWAN, as the coverage is reliable enough.

Furthermore, to demonstrate the LoRaWAN signal quality from publicly available gateways, a TTN Mapper2 tool was used to map the signal quality of LoRaWAN devices near the university building where water meters are installed. TTN Mapper is an open-source application developed by the TTN user community to better address coverage.

The basic functionality of TTN mapping is to combine transmitter location information and signal strength that the transmitter sends to a single publicly available heat map globally.

From this map, general conclusions can be drawn about where more gateways need to be introduced and where the coverage is already good enough to implement a sensor network.

All measurements were performed over a two-day period with the MKRWAN 1300 Arduino device. Measurements were taken between 12:00 and 18:00, which encompassed the most dynamic period of the day in terms of people, vehicles, and other disturbances.

Since an omnidirectional antenna and automatic SF settings were used, the worst-case scenario was covered. The antenna was carried 1.2 meters above the ground as instructed on the TTN mapping page, and the message was sent to the gateway every 35 seconds, ensuring that during the transmission, the person carrying the antenna was not between the antenna and the gateway.

The measurements show signal quality around three publicly available TTN gateways. As can be seen, the signal quality at the university building where LoRaWAN water meters are installed is very good, indicating that LoRaWAN technology can be used to transmit sensor data from a sensor device to a cloud system using publicly available gateways. (Photo: Freepik)