The study of systems and architectures for ambient assisted living (AAL) is undoubtedly a topic of great relevance given the aging of the world population. The AAL technologies are designed to meet the needs of the aging population in order to maintain their independence as long as possible. As people typically spend more than 90% of their time in indoor environments, indoor air quality (iAQ) is perceived as an imperative variable to be controlled for the inhabitants wellbeing and comfort. Advances in networking, sensors, and embedded devices have made it possible to monitor and provide assistance to people in their homes.
The continuous technological advancements make it possible to build smart objects with great capabilities for sensing and connecting several possible advancements in ambient assisted living systems architectures. Indoor environments are characterized by several pollutant sources. Most of the monitoring frameworks instantly accessible are exceptionally costly and only permit the gathering of arbitrary examples. IAQ is an indoor air quality system based on an Internet of Things paradigm that incorporates in its construction Arduino, ESP8266, and XBee technologies for processing and data transmission and micro sensors for data acquisition.
It also allows access to data collected through web access and through a mobile application in real time, and this data can be accessed by doctors in order to support medical diagnostics. Five smaller scale sensors of natural parameters (air temperature, moistness, carbon monoxide, carbon dioxide, and glow) were utilized. Different sensors can be included to check for particular contamination. The results reveal that the system can give a viable indoor air quality appraisal in order to anticipate technical interventions for improving indoor air quality. Indeed indoor air quality might be distinctively contrasted with what is normal for a quality living environment.
MATERIALS AND METHODS
The maximum transmission range between iAQ Sensor and iAQ Gateway was measured at the Polytechnic Institute of Guarda Laboratories Floor using two end-devices and one coordinator as represented in Figure 2. The maximum distance between the end-device and the coordinator is about 27 m considering obstacles between the nodes. In Figure 2, the iAQ Gateaway (Coordinator) is represented by the letter C, and the iAQ Sensor End-device is represented by the letter E.
Therefore, it is possible to construct a modular system that can monitor one or more spaces simultaneously. Figure 5 schematically illustrates the system architecture used in the iAQ. The iAQ Sensor is built using the embedded Arduino Mega system, an open source platform that incorporates an Atmel AVR microcontroller (Atmel, San Jose, CA, USA). In order to allow communication between the iAQ Sensor and iAQ Gate way, ZigBee technology was applied with the use of Xbee modules.
RESULTS AND DISCUSSION
Another important feature of the application is the notification system that can be accessed both on the web portal and the mobile application. Figure 12 shows the Web portal notifications which consists of a list of poor air quality notifications. This data is generated when a monitored parameter exceeds the specified minimum or maximum limit set to reference air quality.
Humans will often be the integral parts of the IoT system; therefore, IoT will affect every aspect of human lives, and IoT technologies provide many benefits to the healthcare domain in activities such as the tracking of objects, patients and staff, the identification and authentication of people, automatic data collection, and sensing. Considering the importance of the air quality in indoor environments, the iAQ web portal allows the user to view the data as numerical values or as a graph. Some of the charts in hand in the web application are shown below, such as the relative humidity chart (Figure 9), the air temperature chart (Figure 10), and the CO 2 chart (Figure 11).
This paper presents iAQ, an air quality monitoring system based on IoT architecture for ambient assisted environments. iAQ was developed using open-source technologies and low-cost sensors. This system incorporates five sensors, but other sensors can be added for specific parameter monitoring. The results show that indoor air quality might be, to a great degree, distinctively contrasted with what is normal for a quality living environment but represents a significant contribution to indoor environmental studies, as it presents itself as a solution for easy installation, is modular, and allows easy access via web portal or from a smartphone to the indoor air quality data while also notifying the user of critical situations of poor air quality.
IoT systems and AAL will continue side by side, mutually contributing scientific advances in assisted living, thereby allowing for a cost reduction in assisted living systems; however, despite the many technologic advances, some difficulties in the construction of assisted living systems continue to exist, in particular, the privacy, confidentiality, and security of such systems. IoT continues to have several QoS (Quality of Service) issues such as availability, reliability, mobility, performance, scalability, and inter-operability. Security and data privacy are the main challenges of IoT. In the future, iAQ should address these problems of the IoT paradigm, creating tools in order to respond to these problems.
Another great advantage of this system is the use of wireless technology for communication between the iAQ Sensor nodes and iAQ Gateway, and wireless connection to the Internet by using Wi-Fi incorporated in ESP8266 as well as a mobile app for Android users to view relevant information and receive notifications anytime and anywhere. The mobile application has the advantage of the use of remote real-time notifications that may help the user to maintain good indoor air quality in a home to increase the occupant’s health, productivity, and well-being.
Source: King Faisal University
Authors: Gonçalo Marques | Rui Pitarma