Active Plant Wall for Green Indoor Climate Based on Cloud and Internet of Things
An indoor climate is closely related to human health, well-being and comfort. Thus, indoor climate monitoring and management are prevalent in many places, from public offices to residential houses. Our previous research has shown that an active plant wall system can effectively reduce the concentrations of particulate matter and volatile organic compounds and stabilize the carbon dioxide concentration in an indoor environment. However, regular plant care is restricted by geography and can be costly in terms of time and money, which poses a significant challenge to the widespread deployment of plant walls. In this article, we propose a remote monitoring and control system that is specific to the plant walls. The system utilizes the Internet of Things technology and the Azure public cloud platform to automate the management procedure, improve the scalability, enhance user experiences of plant walls, and contribute to a green indoor climate.
EXISTING SYSTEM :
The term indoor climate reflects the thermal, atmospheric, acoustic, actinic and mechanical environments of residential, commercial or public buildings, according to the World Health Organization (WHO). The temperature, humidity, air quality and lighting conditions of an indoor space are highly related to human health, comfort perception, well-being and work productivity. Numerous studies have been conducted to reveal negative influences on human-beings who live in contaminated indoor environments . Therefore, the quality of an indoor climate has posed important concerns for people’s lives and health. Many solutions and products have been developed in commercial markets to improve indoor climates, among which the vertical plant wall system is a prominent representative .A plant wall system involves growing diverse types of green plants on a vertically supported system that is attached to an internal or external wall or is designed as a standalone product. A plant wall system consists of vegetation, growing medium and irrigation and drainage systems. In addition to the initial aesthetic decoration, green plants make significant contributions to indoor environments via evaporation, air purification and water retention, which improves indoor climates and reduce energy use . Our previous research has proved that an active plant wall, i.e., a plant wall with an integrated fan to accelerate ventilation, can effectively reduce the main pollutants, such as particulate matter (PM) and volatile organic compounds (VOC), and stabilize CO2 concentrations to a healthy level. Plant walls have been deployed in public spaces, such as universities, airports, museums and offices. However, several constraints hinder plant walls from entering the household market. Regular management of massive plant walls is costly and time-consuming for plant wall suppliers, because vegetation on a plant wall needs professional knowledge of proper plant care. Regular service of plants is also limited by geography because suppliers are unable to serve all consumers worldwide. Thus, reliable and affordable remote management and monitoring solutions for plant walls are in high demand, which is the motivation to this study. In this type of systems, several key factors of an indoor climate, e.g., temperature, relative humidity (RH), CO2 level, and VOC concentration, must be collected and monitored by both consumers and suppliers in real time. By analyzing collected data, suppliers with expertise in planting are able to provide professional feedback to consumers and remotely adjust the watering, lighting and ventilation functions to maintain thriving plants and guarantee a healthy indoor climate. The evolving Internet of Things (IoT) and cloud technologies have become the key enablers to the digitalization of many traditional applications. A number of theoretical and analytic researches have been conducted to promote IoT and cloud technologies into industrial applications . We foresee that a remote management and monitoring system that is based on an IoT and cloud platform can be a viable solution to address the widespread deployment challenge of plant walls. From the integration of sensor networks and cloud infrastructures, remote monitoring solutions that are based on cloud services have been investigated in a broad range of fields, such as industrial monitoring , health care and pain monitoring , traffic monitoring , car parking , agricultural irrigation and environment monitoring .
PROPOSED SYSTEM :
In this paper, we propose and implement a remote monitoring and management solution that is specific to a plant wall system based on the Azure public cloud platform and is aimed at contributing to the indoor climate monitoring and control in public or private buildings. The proposed system consists of both a local control part and a cloud service part. In the local part, a series of environmental parameters are monitored to perceive the indoor climate. The data are continuously fetched and sent to the cloud using the WiFi protocol to ensure security and availability. In our solution, the control functions of watering, lighting and ventilation in a plant wall system are considered. These functions are directly controlled by a local microprocessor according to pre-defined settings that are locally stored and remotely synchronized with the cloud. The cloud part takes advantage of the IoT Hub infrastructure and other services, such as functions, storages and web visualization offered by the Azure platform. Via a web-based user interface, administrators and end users are able to monitor an indoor climate in real time, check historic data from a database, and update the schedules of the pump, light and fan functions, as well as invoke actuators for management purposes. The proposed solution utilizes the Azure public cloud platform to address challenges in terms of security, reliability, scalability and cost.The contributions of this study are as follows:
Proposed a complete solution for remote monitoring and management of plant wall systems. Implemented a local autonomous control unit for plant walls, which consists of both sensing and actuating functions. Developed a cloud solution that is based on the Azure cloud platform, including both back-end and front-end for data storage, real-time monitoring and historic data visualization. Realized remote management and control functions in both the local unit and the cloud via the IoT Hub infrastructure.
This study addresses the critical challenge of digitalization of green technology, e.g., plant walls. The need for remote monitoring and management has become a bottle neck that blocks the widespread distribution of the plant walls and their massive production. In this study, a remote monitoring and management solution that is based on IoT and a public cloud platform is proposed. The system has been completely developed from hardware to software, and from the local control unit to the cloud end. It is capable of performing fundamental plant care functions, such as watering, lighting and ventilation according to user scheduling. Several environmental sensors are integrated and the data are continuously transmitted to the public cloud for real-time visualization and data storage. Via Azure IoT Hub and a web-based interface, administrators and users are able to perform remote monitoring and maintenance. The system has been tested and verified by an experimental deployment. The results indicate that a cloud and IoT-based remote monitoring and management system can be a significant merit to plant walls, in terms of its reliable performance, real-time monitoring, timely feedback and convenient remote control. This solution may greatly benefit plant wall suppliers by simultaneously improving the maintenance efficiency but reducing the cost. The system enables massive and broad deployments of plant walls in public and private buildings and contributes to a green indoor climate in the long term. The IoT and cloud-based solution attains the study goal, i.e., to endow the plant wall system with a digitalized soul. Benefiting from its forward-looking design, this research can also be the starting point towards an intelligent plant wall system in the near future by applying novel data mining and machine learning technologies to the saved historic data to realize adaptive maintenance for the indoor climate. This framework is also applicable to other applications that need remote monitoring and control services.