Design and implementation of an Internet of Things automatic solar shading system

Abstract

The implementation of energy-saving solutions becomes increasingly crucial as global energy reserves decline. The integration of automated solar shading systems not only improves living conditions, but also reduces energy costs. This work presents the design and implementation of an Internet of Things (IoT) automatic solar shading system. The developed solar shading includes custom-made louvers that are able to reflect the external light, while being transparent. Moreover, the system is equipped with a microcontroller and appropriate sensors that enable its automated operation based on measurements of the internal and external environmental conditions. A Raspberry Pi acts as a server, enabling the communication between the shading devices and the users, through an open-source home automation operating system (Home Assistant OS). The user-friendly interface, accessible via a web browser or a mobile application, provides essential data such as temperature, humidity, and device status. Alert notifications are sent when specific conditions are met. The overall system is enclosed in two 3D-printed units, ensuring its durability and easy integration into existing or new installations. In summary, this system combines the advantages of automatic solar shadings, including energy efficiency and improved occupant comfort, with smart features for remote control and monitoring through a user-friendly interface. The proposed system has been installed in a window of our laboratory, performing successfully in real-life conditions.

Keywords

solar shadings Internet of Things microcontroller electric louver solar tracking

1. Introduction

Recent years have seen a global focus on effectively controlling and reducing energy consumption. Buildings play a key role in this aspect, due to their high energy demands. As a result, several studies aim to mitigate this by focusing on decreasing building energy footprint.^1–3 To improve energy efficiency, alternative methods and systems are being explored due to the ever-increasing demand for electricity as a building energy source. One such method involves installing solar shading systems that regulate the amount of solar radiation entering a building, resulting in lower energy consumption and a more comfortable living environment for the residents.

Several studies have demonstrated the significant impact of solar shading devices on various types of properties, including residential, commercial, educational, etc.^4–10 These devices improve indoor thermal conditions, contribute to substantial energy savings and address the challenge of maintaining suitable indoor lighting levels and visual and thermal comfort.^11–17 This challenge is particularly relevant in areas with demanding climate conditions requiring significant cooling energy in summer, and heating energy in winter.¹⁴ Studies have proven that the impact of shading devices on energy requirements of buildings in cities with high solar radiation and high temperature during summer is very crucial. More specifically, the annual energy saving, compared to the absence of shading systems, was approximately 30% in such environments.⁷ Additionally, according to research articles, the use of active automatic shading systems can result in 20% more annual daylight availability, compared to the case of using passive shading systems.^18,19 Moreover, several designs have also demonstrated the advantages of using special materials or coatings that decrease the energy footprint, either by further preventing solar radiation from entering the building, or by harvesting solar energy. One such example is the integration of photovoltaics into shading systems, where traditional shading parts such as panels, blinds or louvers are replaced by or coated with photovoltaic elements.^5,20,21 While these solutions exhibit a minimal energy footprint, it's important to note that photovoltaics are not transparent. Consequently, they attenuate incident light, potentially leading to reduced illumination levels within the building and the formation of shadows. Simultaneously, advancements have been made in transparent-reflective switchable glass technologies; however, the majority of these innovations remain confined to laboratory settings and have not yet been implemented in large-scale architectural constructions.^22–24

Another crucial factor for improved performance of the shading systems is the angle of the louvers, which determines the amount of light entering the building. Ideally, the louvers must be always perpendicular to the incoming light. Thus, automated systems that dynamically adjust their tilt maximize occupant comfort and energy efficiency. In the majority of scientific literature, the dynamic adjustment of louvers is primarily studied theoretically and is not yet widely implemented in existing shading systems.^20,25

Today, with the advancement of home automation technologies, integrating solar shading systems with smart home platforms has become a promising approach to enhance convenience and energy-saving capabilities. This integration allows users to remotely control various home appliances using a Personal Computer (PC), smartphone, or even voice commands. Numerous commercial cloud-based services have been developed to enable remote access to smart devices in buildings. Alternatively, Home Assistant, an open-source platform, offers a range of tools related to home automation. Devices utilizing these services can communicate with a central automation system using communication protocols such as Wi-Fi, Bluetooth and Zigbee, creating a smart ecosystem. Smart devices connected to this network can control different appliances used by building occupants, influencing their comfort and overall energy consumption.^26,27

Existing solar shading systems are often expensive, lack remote control capabilities, and are primarily manually operated, leading to inadequate energy management.^28–31 Implementation, though, of automated shading control systems in office buildings is advocated for energy conservation purposes, supported by several studies demonstrating occupants’ limited engagement with manual adjustments and their preference for automated control.^32,33 Moreover, automatic control systems, in general, play a critical role in optimizing the performance of complex systems by enabling real-time, adaptive responses to changing conditions.^34–37 Additionally, none of these systems incorporate integrated sensors (temperature, humidity, illuminance, etc.) that not only supervise microclimate conditions inside and outside the building but also transform the louvers into smart devices capable of adjusting their position for optimal efficiency. The required sensors and other electronic modules are typically manufactured and sold by third-party vendors, often resulting in compatibility issues and installation difficulties. Furthermore, each module is usually sold as a separate unit, contributing to increased costs, bulky enclosures, and more complex installation procedures.

In recent years, numerous control strategies for solar shading systems have been proposed in scientific literature, including explicit methods based on specific conditions. In most cases, the adjustment of shadings’ angle is typically based on advanced rule-based control (RBC) algorithms, which utilize knowledge of the sun's position for operating shading systems. This method derives from measurements of the sun's azimuth or altitude angle, depending on the orientation of the shading system.³⁸ Alternatively, adjustments may be based on comparisons of internal and external illuminance levels.³⁹ However, existing algorithms lack integration of both conditions, as well as consideration of seasonal and regional variations, which are crucial for optimizing louver tilt angles to achieve optimal illuminance and heating outcomes.^40–44

The objective of this work is to present the design and implementation of a smart solar shading system that can be integrated into new or existing installations. The system utilizes a commercially available motorized shading structure which is improved by integrating sensors that are able to measure several parameters regarding the indoor and outdoor environmental conditions, such as light intensity, temperature, humidity, Ultraviolet (UV) radiation and tilt. The gathered data are handled by a microcontroller and remotely controlled and monitored by a server running on a Raspberry Pi, which also hosts the Home Assistant open-source home automation platform and an MQTT (Message Queuing Telemetry Transport) broker for remote control and sensor data exchange through the MQTT communication protocol. This approach creates a user-friendly platform that wirelessly communicates with the solar louvers, receives and displays sensor measurements, and adjusts the louver's position.⁴⁴ Finally, by placing custom-designed polymer louvers, it was possible to further improve the efficiency of the shading system, by optimizing the reflection of the light. The developed system can be described as an Internet of Things (IoT) device, where data from smart components can be evaluated and transmitted over the internet.

The novelty of such a system lies in its ease of implementation in both existing and new louvers, eliminating the necessity for complex installation procedures. The integrated sensors gather all the necessary data to improve user comfort, and aid in the automation of the louvers’ functions. The utilization of modern microcontrollers with IoT capabilities and user interfaces that can be customized according to user preferences and needs, results in a cost-effective, all-in-one system capable of enhancing occupants’ comfort. Moreover, the presented system is based on efficient algorithms that dynamically adjust the louvers based on sensor readings, calculated sun position, or user preferences. By optimizing the louvers’ position, the building's energy efficiency is also optimized, as demonstrated by our measurements presented in this work.

The following sections will present the system's architecture, the design and development of the complete solar shading system and the initial results of an installed system. The features and performance of the proposed system under real-life conditions will be discussed, highlighting the contributions and potential implications of this research.

2. Methodology and implementation

2.1 Overall design

The proposed solar shading system aims to enhance and automate the functionality of existing or newly developed structures, with minimal adjustments required in their manufacturing process and electrical connections. An essential consideration is the quality-to-cost ratio, which allows for the installation of the proposed system in a wider range of new or existing solar shading structures.

As a result, the system needs to automatically adapt to various weather conditions to provide optimal living conditions for residents. This is primarily achieved by adjusting the position of the shading system in relation to the sun or other light sources. However, manual operation is also necessary to override automatic adjustment when required. Additionally, its remote operation is crucial, enabling users to establish the preferred indoor conditions prior to their arrival.

To meet these requirements, the system relies on sensors, a microcontroller, necessary electronics, and appropriate algorithms. Sensors gather data on essential physical quantities such as light intensity, temperature, humidity, and UV radiation, both inside and outside the building where the shading system is installed. The acquired data is collected by a microcontroller, which processes the information and executes the appropriate actions. Users can intervene to override the system's automatic operation using physical buttons located at the indoor unit or by interacting with the Home Assistant interface that enables remote control and monitoring of the system.

2.2 System's hardware

Based on the described architecture, the system was designed including a microcontroller that possesses sufficient processing power and wireless connectivity. The entire system is divided into two units: the first unit, installed inside the building, houses the microcontroller, power supply, switches, and sensors for indoor measurements. The second unit is positioned externally on one of the louvers to gather data regarding the external conditions, as well as the tilt and position of the louvers in relation to the sun. Communication between the two units is achieved through a wired connection using a standard network cable. While wireless communication between the units is possible, it would require the use of batteries to power the external unit, which is impractical for most installations.

It must be emphasized that the total cost of the developed system was below 100 $€$ , including the sensors, the complementary electronics and the enclosures for the development of one set of indoor and outdoor units. This cost is exceptionally low compared to commercially available solutions utilized in similar systems, which typically offer only a fraction of the measurements provided by our system.

The following sections will outline the selected components for the developed system.

2.3 Microcontroller and sensors

The Espressif Systems ESP32 microcontroller meets the requirements for this project, as it offers a range of features suitable for the designed system. It includes a 240 MHz processor, 520 KB of RAM, and 4 MB of Flash memory, providing sufficient processing power and memory capacity for the system's operations. Additionally, the ESP32 microcontroller integrates Wi-Fi and Bluetooth capabilities, allowing for wireless connectivity, which is also necessary for the specific project.

Furthermore, the ESP32 microcontroller also supports various communication protocols commonly used by sensors, including UART, I2C, and SPI. This ensures compatibility and ease of communication with a wide range of sensors employed in the system.

2.4 Sensors

The optimal performance of the proposed shading system relies on the use of multiple sensors to gather data for decision-making regarding the tilt of the louvers. The first category of sensors is responsible for measuring the basic physical quantities that define the indoor and outdoor conditions of a building. Two breakout boards were utilized for this purpose. These boards incorporate the following sensors: a temperature and humidity sensor (Sensirion SHTC3), an ambient light sensor (Vishay VEML7700), a UV radiation sensor (Rohm Semiconductor ML8511), and a barometric pressure sensor (Bosch BMP280). One board was installed in the indoor unit, while the other was placed in the external unit to enable a comparison between the conditions inside and outside the building.

In addition to these sensors, two light sensors were positioned in the outdoor unit. Their role is to track the position of the sun so that the louvers can be aligned perpendicular to it for optimal shading. Two ambient light sensors (Rohm Semiconductors BH1750) with a separating surface between them were employed for this task. The sensors were mounted on top of the louvers to tilt along with them. When the louvers are not perpendicular to the incident light, one of the sensors detects a higher brightness value than the other. This information is transmitted to the microcontroller, which adjusts the tilt of the louvers until both brightness sensors register similar values.

Furthermore, an Inertial Measurement Unit (IMU) sensor is integrated into the outdoor unit. This sensor comprises a 3-axis accelerometer and magnetometer (NXP Semiconductors FXOS8700) as well as a 3-axis gyroscope (NXP Semiconductors FXAS21002). By combining the data from these sensors, the tilt of the louvers can be determined, providing precise knowledge of the louvers’ position for adjustment. Additionally, the use of an IMU sensor offers the advantage of detecting vibrations through the accelerometer data, serving as a safety feature that prompts the louvers to close in the presence of strong winds.

2.5 Motor control

The AC motor that is typically used for electrically tilted shading system can be easily controlled by relays. For this project, two solid-state relays (SSRs) have been incorporated, that are controlled by the microcontroller to tilt the louvers to the desired angle. Compared with typical relays, SSRs do not have moving mechanical parts that are prone to failure and generate a clicking noise during operation, making them suitable for the specific application.

Nevertheless, the option for manual operation of the tilt is also desired. Three push-button switches are included in the indoor unit. Two of these switches control the opening and closing movements of the louvers, while the third switch allows the user to switch back to automatic mode.

2.6 Packaging

As previously described, the electronics of the system are divided into two units. The outdoor unit, mounted on the louvers, includes two light sensors for determining the optimal louver tilt, a module containing temperature/humidity, UV, and barometric pressure sensors, as well as an IMU sensor for measuring the angle of the louvers and detecting vibrations. The indoor unit houses the microcontroller, a second module of temperature/humidity, brightness, UV, and barometric pressure sensors, two solid-state relays for controlling the AC motor, a power supply, and three switches for manual control.

The enclosures of the two units were designed and 3D-printed using ASA (Acrylonitrile Styrene Acrylate) material. ASA is known for its resistance to water, as well as thermal and mechanical stress, making it suitable for outdoor use. As a result, it is well-suited for the specific application where the outdoor sensors are exposed to varying weather conditions. The design and dimensions of the outdoor and indoor units are presented in Figure 1.

Figure 1.

Drawing of the designed (a) outdoor and (b) indoor units (dimensions in mm).

2.7 Communication and connectivity

The sensors of the proposed system communicate with the microcontroller using either UART or I²C protocols. For the communication between the indoor and outdoor units, a network cable is utilized, which transfers both power and data.

The system architecture incorporates a framework built on a Raspberry Pi, which acts as both a server and a broker, supporting the MQTT connectivity protocol.

To facilitate effective and reliable communication, an open-source home automation platform called Home Assistant is integrated on the Raspberry Pi, running the Home Assistant OS. The user interface is designed to be user-friendly and accessible via a web browser or mobile application. It provides useful information such as the tilt of the shading system and measurements of internal and external temperature, humidity, brightness, and more. Additionally, it allows the switch between automatic and manual operation, by pressing the corresponding virtual buttons of the user interface.

Each message is sent via the MQTT protocol to the Home Assistant environment which is accessible to the user through provided credentials. Thus, the status of the solar shading system and sensor data are monitored on the Home Assistant user interface, providing users with complete remote access to the operation of the louvers. The system architecture, with a focus on communication implementation, is depicted in Figure 2.

Figure 2.

System's communication architecture.

Specifically, the user interacts with the shading system through a Wi-Fi network, due to microcontroller's Wi-Fi capabilities. This enables users to adjust the tilt of the louvers and view the sensor data. Additionally, multiple shading structures within a range of 100 meters can communicate with each other. This allows for the implementation of a Master/Slave communication network, where one shading structure serves as the Master unit equipped with the external sensors, while the remaining shading structures in the same network act as Slaves. Thus, the Slave units are controlled as a group based on the measurements obtained from the Master unit. This approach reduces the cost and complexity of the system, facilitating the adjustment of multiple structures simultaneously.

To ensure system's security, all communication between the microcontroller and the Raspberry Pi is encrypted using SSL/TLS protocols. This ensures that data transmitted over the network is protected from interception and tampering by unauthorized parties. Furthermore, user access to the system is restricted through the use of username/password authentication. Each user can be assigned different roles and corresponding rights, such as Administrator or regular user.

2.8 Developed algorithm

The algorithm that enables the interaction between the hardware and the software of the developed system is written in C++ and is executed by the microcontroller. Its basic functions are related with the communication with each sensor based on the corresponding communication protocols, as well as the establishment of the communication via Wi-Fi, using the appropriate credentials, in order to interact with the MQTT broker. Apart from those typical aspects, the algorithm had to be adjusted to the specific features of this project.

To begin with, the algorithm had to be adjusted regarding the light sensitivity. A slight variation between the measured values of the two light sensors should be ignored. Otherwise, the louvers would be constantly moving, causing excessive energy consumption and occupant discomfort. To address that, a “dead zone” was introduced, corresponding to the absolute difference threshold between the measured values of the two outdoor light sensors. When the difference between the measured values is in the range of the dead zone, no movement is made. Similarly, the option to enable or disable the automatic operation of the system was added, based on a time schedule. In this way, the system can operate only when it is desired, based on the users’ habits.

Another implemented feature of the system is related to the protection of the louvers, in the case of extreme winds. The vibrations occurring due to strong winds can be detected from the embedded accelerometer of the installed IMU sensor. Thus, the algorithm can decide if the louvers must close, to prevent both the shading system and the indoor space.

Furthermore, a backup mechanism was implemented based on the calculated position of the sun, to prevent wrong tilt of the louvers. More specifically, the developed algorithm receives the actual time and date from the Internet and calculates the estimated solar position based on the specific geographical coordinates of the location where the system is installed. As a result, if the light sensors fail or cannot detect any light due to some blocking object, the system will continue its operation based on the calculated data.

Finally, due to the fact that the integrated sensors measure real-time data related to the local weather conditions, an AI-based weather forecast was implemented. More specifically, the data received from the temperature, humidity and barometric pressure sensors are fed to an AI algorithm that predicts the forthcoming weather conditions and generates a related text message that is displayed via the user interface of the developed platform.

The described algorithm is presented below in pseudocode format, highlighting the core operations and logical flow of the interaction between the hardware and software components of the developed system.

2.9 Home assistant server

The Internet of Things (IoT) is an ecosystem, where physical devices can be connected and interact with each other more easily. Via IoT, devices equipped with internet connectivity and sensing capabilities, are now integrated into smart homes, enhancing the comfort and convenience of occupants’ lives. These devices allow users to remotely control their home or workplace environment from anywhere with internet connectivity, monitor its status, and receive useful alerts when necessary.

For this project, the Home Assistant open-source platform has been chosen. Home Assistant is provided free of charge and offers highly customizable settings for automations and user interface (UI) customization. Raspberry Pi can host Home Assistant, acting as a dedicated server, supporting the integration of external devices like the developed shading system. It is also cost-effective compared to other home servers, while having low power consumption.

The first step to integrate the Home Assistant OS to the project was to install it on a Raspberry Pi (model 3B+). The Raspberry Pi, acting as a server, was connected to the local Wi-Fi network, enabling access to the Home Assistant environment, via a web-based UI or the Home Assistant mobile application. Figure 3 illustrates the Home Assistant server running on the Raspberry Pi.

Figure 3.

Raspberry Pi as a Home Assistant server.

2.10 MQTT protocol

To ensure reliable and efficient communication between the shading system's microcontroller and the server, the MQTT protocol is utilized.^45,46 MQTT is a lightweight messaging protocol commonly used in home automation systems, including Home Assistant, for stable communication between low-power devices with minimal network bandwidth. It establishes an instant message delivery system through the publication and subscription of messages within specific topics.

An MQTT broker is set up on Raspberry Pi, to control the distribution of information. The broker receives all messages from publishers, filters them, determines who is interested in them, and sends the messages to the subscribed clients. All devices connected to the platform and using the MQTT protocol for message exchange are considered clients. Subscribers can subscribe to specific topics, and publishers can publish messages to topics accessible by all subscribers.

The solar shading system can subscribe to specific MQTT topics to receive commands from Home Assistant, or it can publish measurements, status updates, and other relevant information as MQTT messages. By using MQTT in Home Assistant, real-time monitoring and control of the solar shading system can be achieved. The ESP32 microcontroller can publish measurements of light intensity, temperature, humidity, and other relevant data as MQTT messages to Home Assistant.

2.11 User interface

Home Assistant⁴⁷ provides a wide range of options for managing and controlling automated systems and smart devices such as the developed solar shading system. Each device or sensor is considered as an “entity” that can be created and managed through the UI, which serves as one of the core elements of the platform. Entities can be created and configured either directly through the UI or by utilizing “Yet Another Markup Language” (YAML) files for more advanced customization.

For the specific project, multiple users were created, each assigned a unique username and password to access the Home Assistant interface and control the shading system. Users can have different roles, with some designated as administrators with full configuration capabilities, while others have limited access and permissions.

The Home Assistant UI can be accessed either through a web browser, or by the Home Assistant application for smartphones. The designed and implemented web and smartphone dashboards of the Home Assistant UI are presented in Figure 4 and Figure 5, respectively.

Figure 4.

Home Assistant web UI.

Figure 5.

Home Assistant smartphone app UI.

These dashboards provide users with the ability to monitor and control the shading system, allowing them to adjust the tilt of the louvers, view sensor measurements, and access other relevant features and functionalities.

The measured data are presented in different panels called “cards”. In this project, several cards have been created to monitor the internal and external environmental conditions of the shading system. One card displays data from external sensors, including temperature, humidity, UV radiation, and more. Another card shows the measurements from sensors placed inside the building, along with the microcontroller. Additionally, a map card has been created to visually represent the geographical position of the shading system. Graph cards are also included in the dashboard, showing the evolution of internal and external temperatures over time.

Another important feature for users is to stay informed about local weather conditions and forecasts. This information is presented in a dedicated card, which can be sourced from an online weather service, or the data acquired by the integrated sensors.

To enhance supervision of the solar shading system, a card has been created to indicate the real-time status of the louvers. This custom-made card provides a visual representation of the louvers’ tilt, allowing users to easily and accurately monitor their position. Figure 6 provides an example of this card, illustrating different angular positions of the louvers.

Figure 6.

Angle State Card in Home Assistant dashboard.

Finally, another card that has been created contains four buttons, each implementing a specific action when pressed. One button sets the shading system to auto mode, another sets it to manual mode, and the remaining two buttons fully open or close the louvers.

3. Results and discussion

To test the proposed design, a prototype arrangement was developed consisting of a solar shading system that is electrically tilted by an AC motor. The dimensions of the structure are 1.4 m in length and 1 m in height.

The outdoor unit (Figure 7), which includes the outdoor sensors, was mounted on one of the louvers. This arrangement allows for the detection of the louvers’ tilt and any vibrations that may affect them, as well as the movement of the light sensors along with the louver, enabling the detection of the optimal angle to ensure that the louvers are perpendicular to the sun.

Figure 7.

The implemented outdoor unit.

The indoor unit (Figure 8) of the solar shading system was powered by the mains, with the AC motor connected to it. This setup enables the indoor unit to provide power to the sensors and control the motor that tilts the louvers without the need of any modifications to the existing procedures of installing an electrical shading system.

Figure 8.

(a) 3D-printed enclosure and (b) electronics board of the indoor unit.

To establish communication between the indoor and outdoor units, a 5-meter network cable was used. This cable is used for both power and data transfer between the two units, ensuring a reliable connection and enabling the exchange of information between the two units.

Figure 9 presents the shading structure and the two units during their lab testing phase. By implementing this prototype arrangement, the functionality and performance of the solar shading system can be assessed and validated. The integration of the sensors and their ability to accurately detect the louvers’ position and external environmental conditions can be evaluated, ensuring that the system operates effectively and provides the desired shading and energy efficiency benefits.

Figure 9.

The electric solar shading system and the indoor and outdoor units.

The system was also tested regarding its communication and user interface. The reliability and efficiency of remote communication were tested by connecting the Raspberry Pi server and a smartphone, accessing the UI through the Home Assistant App, to different networks. The connection between the user's smartphone and the shading system was successful, confirming the effectiveness of the remote communication. All measurements of the indoor and outdoor conditions were logged and remotely accessed through Home Assistant UI. The use of the Home Assistant App for monitoring and controlling the louvers was successful and the louvers effectively responded to remote commands sent to the microcontroller through the application, as depicted in Figure 10.

Figure 10.

Testing the Home Assistant App communication with the solar shading system.

After the initial testing phase, the proposed shading system was installed in a window of the laboratory building, to further test it in realistic conditions (Figure 11). The installed polymer louvers were custom-designed based on prismatic elements, allowing for better light diffusion, while being transparent.

Figure 11.

The proposed shading system installed in a window of our laboratory.

The system demonstrated its ability to adjust the tilt of the louvers based on the direction of external lighting sources, such as the sun. The system successfully logged measurements of the indoor and outdoor conditions, allowing remote access to the data through the dedicated application. The application also provided the capability to remotely control the shading system and adjust its position based on the measured conditions. Moreover, the dead zone related to the movement sensitivity due to the light differences was adjusted. This ensures that the system does not tilt the louvers unless the difference between the measured values of the two light sensors exceeds a specified threshold. Users can adjust this threshold to make the system more or less sensitive to minor lighting variations, such as those that may occur during a cloudy day.

Testing the wind detection feature, which relies on vibration measurements from the accelerometer, proved to be more challenging. The implemented algorithm counts the number of times the acceleration exceeds a threshold value within a predefined time window to detect strong winds. Fine-tuning the threshold and time window values require testing the shading system under various wind conditions, having louvers of different lengths and materials.

By conducting these tests and adjustments, the proposed shading system can be optimized to provide accurate and reliable performance in real-life conditions, ensuring that it effectively responds to external lighting and wind conditions while maintaining user-defined sensitivity levels.

Some challenges in integrating the system into existing buildings include the varying dimensions of windows, which necessitate adjustable louvers, and the requirement of a Wi-Fi connection in the installation area to ensure reliable communication with the server.

To evaluate the efficiency of the developed system, the indoor light intensity and temperature values measured near the window with the automated louvers installed were compared with those measured near a plain window located in an adjacent room, approximately 10 meters away from the first.

The results of these measurements over a period of 12 days are shown in Figures 12 and 13, demonstrating the successful operation of the automated system. More specifically, it is evident that the automated louvers were able to decrease the indoor light intensity to approximately 50 lux. Similarly, a reduction of approximately 2 ^oC was observed inside the room where the same system was installed.

Figure 12.

Comparison between outdoor and indoor light intensity measurements taken near a plain window and a window with the shading system installed, over a 12-day period.

Figure 13.

Comparison between outdoor and indoor temperature measurements taken near a plain window and a window with the shading system installed, over a 12-day period.

Preliminary results regarding the energy efficiency improvements achieved through the installation of this system are illustrated in Figures 14 and 15. These figures depict energy usage and losses across various categories in the building, comparing conditions without the proposed system (Figure 14) to those with the system installed (Figure 15). The graphs provide a comprehensive overview of the system's performance, presenting energy gains (positive values) and losses (negative values) over a one-year period, measured in kilowatt-hours (kWh).

Figure 14.

Energy usage and losses without the proposed automatic solar louver system over a year.

Figure 15.

Energy usage and losses with the proposed automatic solar louver system over a year.

From this comparison, it can be concluded that the building's energy consumption without the system is more than twice as much as that observed when the system is installed.

4. Conclusion

This paper presents a robust and user-friendly cloud based IoT automatic solar shading system that utilizes a microcontroller, a Raspberry Pi server, and the MQTT connectivity protocol integrated with the Home Assistant home automation platform. The system offers remote control and monitoring capabilities for a solar shading system, providing essential data such as temperature, humidity, and tilt to the user interface dashboard. The system's architecture and communication protocols are designed for efficiency and scalability, making it adaptable to different building types and sizes. The user interface is accessible through the web or mobile applications, ensuring ease of use for end users on various devices and operating systems.

The implemented system has been successfully tested and installed in a real-life environment, demonstrating its expected operation and effectiveness. It offers improved energy efficiency, enhanced occupant comfort, and convenient remote control and monitoring features. By integrating sensors and a microcontroller, the system optimizes the indoor conditions by automatically adjusting the tilt of the louvers based on environmental factors. Users can also manually control the shading system and view real-time data through the dedicated application.

The proposed solution holds promising potential for practical applications in the field of smart building automation. By reducing energy consumption and improving living conditions, an automated solar shading system contributes to sustainable and comfortable environments. Overall, the developed system represents a valuable contribution to IoT-based solar shading systems, offering a cost-effective and scalable solution for improving energy efficiency in buildings.

Footnotes

Acknowledgements

This research has been co-financed by European Union and Greek national funds through the Regional Operational Program Sterea Ellada 2014–2020 under the call “Support of Plans for Research, Technological Development, and Innovation in RIS3 sectors of the Region of Sterea Ellada (project code: ΣΤΕΡ1-0025535).

ORCID iD

Georgia Stamou

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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