Recent advancements in information and communication technology and the Internet of Things (IoT) have increased the number of sensors used in smart cities. Collecting and analyzing enormous amounts of data from connected devices in homes and cities has emerged as a significant study area. At the same time, algorithms for machine learning have been deployed to learn and analyze data collected from various sensors to classify and predict trends in smart homes and cities. Several factors have contributed to the popularity of utilizing algorithms for machine learning in today’s society. Three primary aspects inspire the use of machine learning [1]: (a) computers have high performance and memory; (b) machine learning algorithms learn and train on behavioral patterns resembling the human brain; and (c) huge datasets available.

Therefore, collecting environmental datasets is essential for monitoring environmental conditions and gaining knowledge of the environment’s state in any country, including Saudi Arabia. Deserts, mountains, coastal regions, and marine environments are only a few of the ecosystems that may be found in Saudi Arabia. As a result, collecting data on the environment in Saudi Arabia is essential for various reasons. To begin, it might help identify environmental problems such as pollution, the degradation of habitats, conditions affecting healthcare, and the implications of climate change. Scientists and officials can comprehend the environment’s condition better and make informed decisions about how to handle environmental challenges if they acquire data on the quality of the air and water, changes in the environment, and the distribution of animals. Second, collecting data on the environment may assist in keeping track of the movement toward environmental objectives and targets. Researchers may improve their knowledge of the dynamics of ecosystems, their ability to anticipate changes in the environment, and their ability to recommend solutions to environmental issues by using environmental data. For instance, Saudi Arabia has vowed to drastically decrease its emissions of greenhouse gases by 2030 drastically and to significantly raise the percentage of its total energy supply that comes from renewable sources. Collecting energy use, emissions, and renewable energy generation data may help track progress toward these objectives and identify areas where extra action may be required. Last but not least, collecting environmental data may facilitate research and innovation in various sectors, such as healthcare, smart cities, ecosystem, climatology, and environmental engineering.

Collecting environmental data is a crucial component of environmental management and holds significant importance in Saudi Arabia, which is confronted with various environmental problems. The nation has been facing noteworthy air pollution challenges due to industrialization and urbanization, which have led to increased health and environmental concerns [2]. Furthermore, the nation depends mostly on wells in water supply [3]. Moreover, the climate varies from city to city. Temperatures may reach over 40 degrees in the summer season. At the same time, the temperature could reach below zero degrees in the northern cities. In response to the environmental challenges, Saudi Arabia has undertaken various environmental initiatives such as the Saudi Green Initiative and the Green Middle East Initiative. These initiatives are designed to mitigate greenhouse gas emissions, conserve natural resources, and enhance renewable energy production [4]. The efficacy of these endeavors is contingent upon the accurate and reliable collection of environmental data. Environmental data collection in Saudi Arabia is presently conducted by various governmental and non-governmental entities, such as the Ministry of Environment, Water, and Agriculture, the General Authority for Meteorology and Environmental Protection, and the Saudi Arabian Society for Environmental Sciences [5]. These entities gather ecological information on various parameters, including but not limited to the environment and water-based quality, soil and land use, and biodiversity.

Saudi Arabia has to deal with the problem of urbanization, as over 85% of its population resides in urban areas, as per the studies conducted by [6]. This is in addition to the environmental challenges that the country is dealing with. The nation is addressing the challenges of urbanization by creating intelligent cities, such as Neom and Riyadh, that strive to leverage technology and data to enhance the prosperity of citizens and promote sustainable development [7]. In addition, collecting environmental data is crucial in advancing smart city initiatives. Monitoring and mitigating urban heat island effects in cities can be facilitated by collecting air quality, temperature, and humidity data. According to [8], collecting energy usage and emissions data can optimize energy consumption and mitigate greenhouse gas emissions within smart urban areas. In addition, collecting environmental data is important for meeting healthcare needs in Saudi Arabia. Environmental factors such as air pollution, water contamination, and poor sanitation can substantially affect public health. Collecting environmental data can identify possible risk factors and provide valuable information for developing public health policies and interventions to mitigate these risks. An investigation was carried out to examine the effects of air pollution on public health in the city of Jeddah through the collection and analysis of relevant data [9]. The authors of [10] revealed that the prevalence of respiratory and cardiovascular diseases was linked to elevated levels of air pollutants in Jeddah. The above data was utilized to develop policies and interventions that focused on enhancing the air quality within the urban area. These measures included the mitigation of emissions from both transportation and industrial sources.

In light of the growing interest in smart homes and cities, researchers have attempted to incorporate different aspects of urban life into smart homes and cities through important technologies, including the IoT paradigm, wireless sensor networks, embedded systems, and other related technologies. Machine learning algorithms have various potential applications in smart home and city environments, including dealing with problems related to healthcare, power consumption, and automation. To effectively apply machine learning algorithms for various applications, it is necessary to have a dataset representative of the problem domain for training and testing purposes. The dataset demonstrates the potential for evaluating and validating the proposed method’s accuracy. Although many real-world datasets are publicly accessible, some lack adequate physical factors such as temperature, humidity, pressure, and altitude. It reads data from sensors that can be noisy, has poor network conditions, and is subject to several unknown variables, such as missing data and faulty sensors. Consequently, it is prone to errors that affect the accuracy of the data.

As seen from the previous discussion, there are some efforts either from the authorities or researchers in environmental data collection in Saudi Arabia. However, the focus was on the outdoor environment. There is a lack of indoor environment data collection; to our knowledge, no dataset is already available for researchers. The dataset was generated using the Arduino integrated development environment (IDE), an open-source electronics platform that uses hardware and software. It includes several sensors on a board that can generate data using light, temperature, humidity, and other sensors. The dataset was generated from real sensors to measure physical variables in a home for one month. The dataset contains five features representing temperature, humidity, pressure, light, and altitude. It records measurements of physical variables in real time.

2. Indoor Environmental Parameters in Northern Saudi Arabia