The Implementation of IoT Sensors in Fog Collector Towers and Flowmeters for the Control of Water Collection and Distribution

Abstract

This study describes the implementation of Internet of Things (IoT) sensors in flow meters installed in drinking water systems and in fog catchers built in low-income, high-altitude communities in the Andes region of Ecuador, taking studies at the University de las Fuerzas Armadas ESPE as our reference. The influence and management of these intelligent sensors are analyzed, as well as a basic review of the materials and methods used in their implementation. The importance of validating the accuracy and reliability of IoT sensors compared to professional devices is highlighted, especially in mountain areas with difficult access. Additionally, the cost–benefit of using IoT sensors in fog catchers and drinking water distribution networks is mentioned, which depends on several factors such as the scale of the project, the objectives to be achieved concerning monitoring, and the available resources. Finally, it is highlighted that using Internet of Things (IoT) sensors in construction and water collection systems has proven beneficial in detecting possible effects on its operation and determining consumption and supply flows for a given population.

1. Introduction

The advancement of technology and connections through the network in IoT sensors, such as virtual data storage, allows real-time monitoring of any ecosystem, whether it is irrigation, construction, or supply [1,2,3].

IoT devices installed in hydro sanitary construction systems enable risk prevention during operation and control of the operational flow to make long-term predictions, aiding in the analysis of consumption behavior for a given beneficiary population [4]. In this case, IoT sensors with network connectivity were installed in fog catchers for water collection in areas with difficult access to the resource, and in intelligent flow meters as part of the drinking water distribution network for consumption at the same university [5,6,7,8,9,10,11,12,13]. Their inclusion is a cost–benefit solution and an alternative to building hydraulic works in complex sites or detecting system failures through on-site destructive tests [14,15]. Additionally, monitoring water consumption in an institution with groundwater wells helps quantify the water extracted versus what the well can provide during its useful life, preventing permanent drying up. Another important case is determining the real minimum and maximum endowment based on daily consumption by the saturation population at the university.

Another important point is the growth in the use of IoT flow meters for wastewater management, which allows precise control of volume and flow through the Internet [16], providing direct data on actual conditions and facilitating more efficient tracking and more accurate trend analysis. Integration with IoT also enables advanced automation solutions, improving operational accountability and management efficiency [17].

In Ecuador, there are populations in high-altitude areas where water resources are difficult to access, prompting researchers to develop new technologies to address this problem and control operations through historical data, such as installing IoT sensors to monitor the volume of water captured in fog catchers.

The SAPSYB standard in Ecuador for rural and urban areas stipulates that a drinking water installation is designed for a period of 20–25 years in continuous operation. Therefore, in large complexes such as a university, it is important to know the system’s status when it completes its design period. New technologies, such as implementing IoT flow meters at strategic points to measure flow and control discharges, support hypotheses about the system’s current state, and estimate non-revenue water (NRW), a crucial factor for formulating solutions.

The lead author of this work has published theoretical and experimental research pioneering the practical application of IoT sensor systems in water resource management. Unlike other theoretical studies, the research presented here successfully used smart sensors installed in systems such as fog trap towers and smart flow meters in real environments in Ecuador. These implementations have proven to be effective and cost-effective strategies for water monitoring and management, especially in low-income communities. The accuracy and reliability of these devices highlight the innovative and sustainable impact of the lead author’s work, significantly differentiating it from other researcher’s efforts.

The objective of this work was to describe the performance of IoT sensors installed in water collection systems such as fog catchers in low-income communities in Ecuador, as well as the use of IoT flow meters in the drinking water network at the University of the Armed Forces ESPE, by monitoring and obtaining data in real time. The study design came about through meta-analysis and systematic search of related works, mainly results obtained in studies and practical projects where prediction models were generated to capture water from fog and monitoring of the amount of water that can be generated in various regions of Ecuador, highlighting the profitability of the trap systems compared to traditional drinking water systems. Finally, we compared our results with those from previous projects related to the design and installation of IoT flow meters in the drinking water network, where consumption patterns and anomalies were identified, allowing the establishment of a smart university’s resource distribution.

2. Applied Study Methodology

To obtain information, a systematic search was used based on data obtained from research by Scopus, Science Direct, and Web of Science, which allowed the identification of relevant studies on the implementation of IoT sensors in drinking water systems and fog towers in low-income communities [4]. Subsequently, a meta-analysis was carried out to synthesize the findings and obtain updated references on the performance, feasibility, and effectiveness of IoT sensors in the collection and distribution of water in various contexts.

Meta-analysis, considered a statistical technique used in scientific research, allows the combination and analysis of results of multiple independent studies on a specific topic. In relation to the review of individual studies, this methodology allows researchers to integrate data from various related studies, thus obtaining a more accurate estimate of the effect or relationship between variables [18].

Despite its usefulness, the success of a meta-analysis is strongly influenced by the number and quality of available studies. While there is no predetermined minimum number for conducting a meta-analysis, those with a larger number of studies are considered more reliable and tend to produce consistent results regardless of observed variability [19].

The area of influence and the population to which the application of different intelligent systems is focused are detailed below.

3. Influence and Management of IoT Sensors in Drinking Water Systems

Studies were conducted in the hydrosanitary system of the University of the Armed Forces (ESPE) headquarters campus in the valley of Los Chillos, province of Pichincha, northwest of Sangolquí, in the highlands region of Ecuador (Figure 1). The specific location is on Av. General Rumiñahui S/N and Ambato Santa Clara sector [12].

Projects at the institution focus on analyzing the consumption and discharge of the drinking water supply versus the wastewater network to determine the percentage of non-revenue water (NRW). The drinking water network, starting from the storage cistern that supplies most of the university campus, has four flow meters installed: in Block B, in the Administrative Building, in Block C, and a new one installed in 2024 monitoring the university’s library. The wastewater network has three discharge points, controlling the levels of water going to the public sewer within the university grounds [13].

Implementing IoT flowmeters in the network of the main buildings of the University also made it possible to identify the levels and periods of highest consumption of drinking water generated by the saturation population made up of 9785 students, professors, and administrative staff [13] during the 7 days of the week. With these data, consumption graphs and dynamic models (time series) are created to determine if there is increasing consumption and prevent possible problems in the supply of the resource.

Projects related to consumption vs. waste discharges also make it possible to identify anomalies or fractures in the drinking water network due to the age of the hydrosanitary system [11]. It is presumed that, with the values of non-revenue water (NRW) of each of the studies carried out in the institution, data and conclusions can be supported with ground-penetrating radar or geophone studies.

4. Influence of IoT Sensors on Fog Collector Towers

The availability and distribution of freshwater resources in the world show great scarcity that affects many regions due to various environmental and social factors, such as changes in geography, climate change, migration of populations, and changes in water supply and use. To this end, a priority approach has been made so that the search for new and modern water supply systems can be achieved through the construction of infrastructures such as pipelines, dams, aqueducts and treatment plants. In addition, innovative technologies and applications are being explored to supply water to arid or dry regions that have historically been neglected or excluded from central distribution systems [9].

Managing and adapting to drought is crucial in Ecuadorian provinces with little rainfall at certain times of the year. Lack of precipitation can have negative consequences on the availability of water, both for human consumption and for agriculture, and can create significant challenges in terms of water security in these regions. In this sense, one of the new applications to increase the supply of fresh water has been based on the capture of water in the form of fog in high mountainous regions [6,7,8]. A fog catcher is a structure created for the purpose of collecting moisture from the air, especially in dry or semi-dry areas where the water supply is limited. These structures are very useful in environments where there is little rainfall and obtaining water is a challenge. The main purpose of a fog catcher is to collect the small water particles present in the fog and condense them into larger droplets that are then collected and directed towards storage containers. This ingenious approach harnesses moisture in the air for drinking water or for irrigation in areas where other water sources are limited.

The proposed misting systems may not fully meet the needs described above: communities do not need to obtain 100% of their water from the misting for irrigation, but a certain amount allows them to irrigate crops on days when water is scarce and there is not enough for their agricultural production to develop on a regular basis [14].

Several rural areas of Ecuador have benefited from the implementation of this new technology (Figure 2), such as Galte, a community located in the province of Chimborazo, within the Guamote canton in the Palmira parish, located at a minimum altitude of 3200 m above sea level. The main economic activity of Galte is agriculture. These indigenous communities inhabit a region known as the “Palmira desert”, which suffers from water scarcity. The other area of study is the province of Pichincha, in the Quito canton, identifying as the main area the Ilaló volcano located 8 km from the city. It constitutes an important geographical barrier that is home to a significant amount of biodiversity and has its own characteristics with a local microclimate [5]. This would benefit the optimization of water collection and the monitoring of the performance of the mist collectors. The information collected by IoT sensors could be used to adjust the location and orientation of fog towers, as well as to perform preventive and predictive maintenance, which would help maximize atmospheric water collection.

5. Materials and Methods

5.1. Implementation of IoT Sensors in Flowmeters

In 2021, IoT sensors with internet access were implemented to measure the volume of water flowing through a drinking water pipe by reading pulses. This device uses a water flow control meter that features an LCD display or quantitative liquid controller, supplemented by the programming needed to send the collected data to the cloud. These data are reflected in smart devices connected to the internet [12].

Previously, only one IoT device was available in the administrative building. However, the implementation of another similar device was carried out in Block B (Figure 3 and Figure 4), with the collaboration of students studying Installations in Smart Buildings, who were supervised by Engineer David Carrera, PhD. The devices were synchronized with the online platform https://thingSpeak/ and http://thinger.io/ (accessed on 30 July 2024) and a verification of the condition of the pipes in Blocks A, B, C, and D was carried out. In addition, the availability of the Wi-Fi network was evaluated to avoid possible data loss due to a poor signal. A verification of the diameter of the pipes was also carried out to ensure compliance with the technical specifications [13].

In 2023, a new IoT flowmeter was implemented in the supply network of Block C, under the command of MIC students and their supervisor, Engineer David Carrera, PhD., completing 3 IoT flow meters that will allow more accurate values of sectorized water consumption to be obtained throughout the University.

5.2. Implementation of IoT Sensors in Towers of Fog Collectors

The implementation of IoT sensors in fog catchers allows remote and real-time monitoring of different parameters such as humidity, temperature, and wind speed and direction, among others, which helps to optimize the efficiency of water collection and to accurately track the performance of fog collectors. The location of each mist catcher was selected considering a maximum radius of 150 m around the community house in the Galte population so that the collection water supply point remained easily accessible [9].

The construction of the fog catchers was accomplished with alternative materials, including the main material, reeds. Other materials that were used in the construction were galvanized steel pipes with a 3/4″ cross-section and a thickness of 1.5 mm, 50% polyester mesh and 65% shade, #18 galvanized wire, an ice axe, rope, plastic ties, and a plastic collection tank of 0.2 m³ and 0.5 m³ capacity.

The thicker-section reeds were located in the lower modules (modules that serve as bases and support a greater load from the tower). Reeds with a smaller cross-section should be used for the modules that go at the top of the tower to reduce the weight of the structure at the top [8].

The implementation of the IoT platform is based on Long-Range Radio (LoRa) for communication. This means that it is composed of terminal nodes or sensors that capture information on environmental variables and the amount of water captured. These nodes are centralized in a “Lora Gateway” a gateway that receives the data from the nodes through a Radio Frequency (RF) signal and through a Wi-Fi signal to forward the data obtained as a web service to a database within a server hosted in the cloud (Microsoft Azure, academically licensed platform from the university). In this way, the data can be monitored remotely and products can be generated with the information obtained. Figure 5 shows the architecture of the IoT ecosystem [8].

Sensors were selected to measure various weather conditions, considering factors such as measurement range, communication protocols, availability, and costs. The variables monitored include wind speed, atmospheric pressure, temperature, relative humidity, visibility level, light, and, crucially, the level of liquid collected, for which a level sensor was used. The specific details of each sensor are found in

Table 1. Sensor specifications.

Variable	Model	Communication Protocol	Units	Precision	Measuring Range
Pressure	BME280	12C	hPa	±10	-
Humidity	BME280	12C	%	±15%	0–100%
Temperature	BME280	12C	°C	±0.5	−9 °C–65 °C
Light	GA1A12S202	12C	Luxes	±5	3–55,000
Fluid level	e-tape liquid level-PN-12110215TC-12	Male Crimpflex Pins	(m)	25 mm	0–75 cm
Wind speed	anemometer wind speed sensor W/Analog Voltage Output	-	m/s	1 m/s	0.2–50 m/s
Level of visibility	MiniOFS	5-wire cable	km	+5	20 m–400 m
Date and time	DS3231	12C	-	-	-

[8].

5.3. Cost–Benefit Ratio

The benefit of using IoT sensors to monitor water quality and distribution allows data to be collected remotely and in real time, which facilitates the early detection of problems in the network where they were installed [15]. In addition, IoT sensors are low cost and can make monitoring more accessible in situations where the project does not have a large monetary backing. However, the accuracy and reliability of IoT sensors lie in their cost compared to professional equipment to ensure the data are collected. Its easy access to long-range Wi-Fi connectivity and Bluetooth highlights the ability to visualize data in online databases and suggest action protocols to users in case of any anomaly, as well as the possibility of dynamic monitoring modules [3,10].

The cost–benefit of using IoT sensors in fog catchers will depend on several factors, such as the scale of the project, specific goals, and available resources. However, we can consider aspects such as accurate monitoring of variables, e.g., wind speed, temperature, humidity, etc. We can also consider operational efficiency by leveraging real-time information provided by the sensors to optimize fog catcher operation. In addition, it will help save resources by adjusting the operation based on real-time data, which facilitates research [1,10].

Fog collection technology is a low-investment technique that dispenses with electrical power and has significantly lower operating costs compared to conventional water supply systems. Unlike the latter, which requires a large initial investment and generates ongoing expenses for fuel, spare parts, and maintenance, fog water harvesting is relatively cost-effective in areas where it is feasible. As a result, it is possible to supply the needed quantities of water to beneficiary communities efficiently and at a lower cost [10].

6. Results Obtained Due to the Implementation of IoT Sensors

6.1. Smart Water Collection System

In the Community of Galte, located more than 3500 m above sea level, a fog catcher tower was implemented in two directions to capture water for cultivation, obtaining an average of 1.91 L/m²/day. Thus, even in other designed towers, the levels of captured water can be monitored as shown in the

Table 2. Monitoring of water levels captured in different fog trap towers built.

No.	Model	$\mathbf{Peak}\mathbf{Performance}\mathbf{L}/{\mathbf{m}}^2$/Day	$\mathbf{Average}\mathbf{Performance}\mathbf{L}/{\mathbf{m}}^2$/Day	$\mathbf{Minimum}\mathbf{Performance}\mathbf{L}/{\mathbf{m}}^2$/Day
1	Galte	2.63	1.91	0.65
2	Fog collector in two dimensions	1.33	0.87	0.33
3	Farm Urku Huayku	4.57	0.56	0.07
4	Italo mountain	0.85	0.23	0.1
5	Conocoto Quinta Girasoles	2.52	0.42	5.0
6	Conocoto Parque Metropolitano del Sur	2.20	0.25	0.10
7	Bunche	0.80	0.40	0.00

[10].

These data allow verification of the amount of water recovered from the fog in each tower, which is an important contribution in mountain communities with difficult access to water catchment, and where it is essential to measure how much water can be obtained to supply the community and prevent the system from collapsing in the future due to an increase in the population. In this case, solutions can be proposed in advance. Such data can be obtained thanks to the implementation of Internet of Things (IoT) sensors in the water catchment system.

6.2. Data Obtained by IoT Flowmeters

In real time, the flowmeter measures the flow of water every 20 s, then the real-time data obtained are saved and monitored through the thinger.io platform, in which it is possible to identify failures in the measurement or disconnection of the equipment (Figure 6).

Below is the University’s water consumption analysis interface for the administrative buildings and Block B [11], obtained from the digital platform where the measurements are automatically saved (Figure 7).

Once the data were downloaded and processed in an electronic sheet, we had the following table, in which the consumption in liters per day is framed [11] (Figure 8).

With such data, time series, recurrence maps, and comparative graphs of consumption in days, months, or hours can be created, as was the case in 2021, in the study carried out by engineer Rodney Garcés and engineer David Carrera Villacrés PhD. [2], for which the map of recurrences for February–November 2021 is presented (Figure 9).

7. Results Obtained from the Systematic Search

Studies carried out in different parts of the planet on the use of IoT sensors are presented. However, most of the published projects are related to the application and control of water in drinking water networks and its capture by means of fog catchers, without highlighting the use of Internet of Things (IoT) sensors (

Table 3. Research related to the use of IoT sensors for water management in conduction and catchment.

	Title	Ref.
IoT Flowmeter	Recording Wastewater Treatment Plant Outlet Water Discharge Using Google Sheets	[17]
	Prototipo funcional IOT para determinar la viabilidad de instalación del modelo atrapanieblas tipo chileno en el municipio de Chiquinquirá Boyacá	[20]
	Sistema IoT para el análisis de calidad de agua	[4]
	Automation of Residential Water Flowmeter	[16]
	Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning	[21]
	Water contamination analysis in IoT enabled aquaculture using deep learning based AODEGRU	[22]
	Internet of things sensors and support vector machine integrated intelligent irrigation system for agriculture industry	[23]
	Critical review on water quality analysis using IoT and machine learning models	[24]
	Internet of Things (IoT) enabled water monitoring system	[25]
	Building a Smart Water City: IoT Smart Water Technologies, Applications, and Future Directions	[26]
Tower Fog Collector	Diseño e implementación de torres atrapanieblas (3d) y ecosistema informático de monitoreo con internet de las cosas y aprendizaje automático	[8]
	Potential Solutions for the Water Shortage Using Towers of Fog Collectors in a High Andean Community in Central Ecuador	[9]
	Fog Collectors Systems with IoT Sensors in the Andes and Coastal Regions of Ecuador South-América and Data Processing	[10]
	A proposed standard fog collector for use in high-elevation regions	[6]
	Eficiencia de captación de agua con tres tipos de malla atrapanieblas en zonas rurales altoandinas de la sierra norte del Perú	[27]
	Smallness and Small-device Heuristics: Scaling Fog Catchers Down and Up in Lima, Peru	[28]
	Fog water traps as a low-cost alternative source of water in coastal desert areas of the pacific.	[29]
	Atmospheric water collection using Three Types of Fog Catchers for high Andean climatic conditions, case: locality 22 de Mayo-Celandines-Perú	[30]
	Fog catchers and water collection in a Colombian paramo ecosystem Colectores de niebla en un páramo Andino	[31]

).

8. Discussion

The use of IoT sensors to monitor the levels of functionality of a construction system makes it possible to prevent effects on its operation now and in the future, taking into account that each construction system has a design period and that when it is fulfilled it is important to maintain real-time control, as is also the case with intelligent water collection systems for mountain areas [9]. By implementing intelligent IoT sensors, it implies that it has an internet connection all the time to maintain the upload of data to an electronic cloud constantly; a failure in its connectivity requires an operator who knows the operation of the integral system to attend the site for reconnection [15].

Table 3 shows the most relevant work carried out worldwide on the implementation of IoT sensors in both flowmeters and fog catchers, however, as this is an innovative technique, there is not enough information on the subject, so the number of articles and real monitoring data are not enough to carry out the meta-analysis with an acceptable degree of reliability.

Engineer David Carrera, PhD has, during the last few years, taken the initiative to implement intelligent water catchment systems in high-altitude areas of Ecuador such as fog catchers using IoT sensors for monitoring operations. This is in addition to supporting the study of the drinking water network at the University of the Armed Forces (ESPE) Campus Matriz in Sangolquí, Ecuador through the installation of IoT flow meters with connection to the network, allowing real-time consumption data to be obtained at the main points of the institution, and which serve to allow analysis of the consumption and current state of the network since it has fulfilled its optimal design period.

9. Conclusions

The implementation of Internet of Things (IoT) sensors in drinking water systems and fog catchers in low-income communities in Ecuador has proven to be an effective and promising strategy for managing this vital resource. Real-time monitoring has validated the accuracy and reliability of these devices, highlighting their potential to generate predictive models and improve decision-making in environments where access to water is limited or scarce. In addition, the use of IoT sensors in construction and water collection systems offers a cost-effective alternative to guarantee efficient operation and prevent potential effects such as leak detection and increases in resource consumption. Ultimately, this research provides new perspectives for improving water management in vulnerable communities, offering innovative and sustainable solutions to address the challenges of access to drinking water, underscoring the importance of technology in creating a more equitable and sustainable future for all.

In this context, the previous work of the lead author of this study has pioneered the practical application of flowmeter and fog catcher systems. These efforts have laid the foundation for current implementations of IoT systems, providing an essential framework that has enabled the development of innovative and sustainable solutions for water management. The combination of these technologies has provided new perspectives for improving water management in vulnerable communities, underscoring the importance of technology in creating a more equitable and sustainable future for all. The research highlights how a continuous advance in this area can offer practical and efficient solutions to the constant challenges regarding people’s access to drinking water, thus confirming the relevance and impact of the pioneering works of the main author of this work.