Raising awareness for water polution based on game activities using internet of things

Awareness among young people regarding the environment and its resources and comprehension of the various factors that interplay, is key to changing human behaviour towards achieving a sustainable planet. In this paper IoT equipment, utilizing sensors for measuring various parameters of water quality, is used in an educational context targeting at a deeper understanding of the use of natural resources towards the adoption of environmentally friendly behaviours. We here note that the use of water sensors in STEM gameful learning is an area which has not received a lot of attention in the previous years. The IoT water sensing and related scenaria and practices, addressing children via discovery, gamification, and educational activities, are discussed in detail

An IoT-based solution for monitoring a fleet of educational buildings focusing on energy efficiency

Raising awareness among young people and changing their behaviour and habits concerning energy usage iskey to achieving sustained energy saving. Additionally, young people are very sensitive to environmental protection so raising awareness among children is much easier than with any other group of citizens. This work examinesways to create an innovative Information & Communication Technologies (ICT) ecosystem (including web-based, mobile, social and sensing elements) tailored specifically for school environments, taking into account both theusers (faculty, staff, students, parents) and school buildings, thus motivating and supporting young citizenś behavioural change to achieve greater energy efficiency. A mixture of open-source IoT hardware and proprietary platforms on the infrastructure level, are currently being utilized for monitoring a fleet of 18 educational buildings across 3 countries, comprising over 700 IoT monitoring points. Hereon presented is the system's high-level architecture, as well as several aspects of its implementation, related to the application domain of educational building monitoring and energy efficiency. The system is developed based on open-source technologies andservices in order to make it capable of providing open IT-infrastructure and support from different commercial hardware/sensor vendors as well as open-source solutions. The system presented can be used to develop and offer newapp-based solutions that can be used either for educational purposes or for managing the energy efficiency ofthebuilding. The system is replicable and adaptable to settings that may be different than the scenarios envisionedhere (e.g., targeting different climate zones), different IT infrastructures and can be easily extended to accommodate integration with other systems. The overall performance of the system is evaluated in real-world environment in terms of scalability, responsiveness and simplicity

Smart cities air pollution monitoring system - Developing a potential data collecting platform based on Raspberry Pi

>Magister Scientiae - MScAir pollution is becoming a challenging issue in our daily lives due to advanced industrialization. This thesis presents a solution to collection and dissemination of pollution data. Most of the devices that monitor air quality are costly and have limited features. The aim of this study is to revisit the issue of pollution in cities with the aim of providing a cheaper and scalable solution to the challenge of pollution data collection and dissemination. The solution proposed in this paper uses Raspberry Pi and Arduino micro-controller boards as the foundation, combined with specific sensors to facilitate the collection and transfer of pollution data reliably and effectively. While most traditional air pollution monitoring equipment and similar projects use memory cards as a medium for data storage, the system proposed in this research is built around a new network selection model that transfers data to the server by using either Bluetooth, Wi-Fi, GSM, or the LoRa protocol. The connectivity protocol is selected automatically and opportunistically by the network selection algorithm defined in the micro-controller board. The final data will be presented to the user through a mobile application and website interface effectively and intuitively after being processed in the server. This data transfer system can effectively reduce the cost and input of human resources. It is a viable solution. For other environmental research, this system can provide an air quality data support for analysis and reference. Modularity and cost-effectiveness are fully considered when designing the system. It is a viable solution. We can generalize the system by slightly changing the data transmission modules. In other case, it can be used as a platform for similar data transmission and offer help for other research directions

The Economics of the Internet of Things in the Global South

While the Internet of Things (IoT) is not new, its key components are becoming increasingly affordable now, which makes the technology extremely attractive for the Global South. By collecting data from various IoT sources, combining them with data from other sources and using big data analytics, decisions can be made and actions can be taken that can have important economic, social, ecological and environmental implications in these countries. The most visible impacts of the IoT in these countries include improvements in agricultural and food systems, enhancement of environmental security and resource conservation, achievement of better healthcare, public health and medicine, and enhancement of the efficiency of key industries. This paper provides an overview of how the IoT is currently being used in the Global South. It also discusses the opportunities and challenges that IoT initiatives present there. The analysis indicates that the IoT may address some of the institutional bottlenecks, technological challenges and key sources of high transaction costs. On the other hand, various sources of underdevelopment may act as barriers to full utilisation of the IoT

A Proposal for Architectural Framework Using Internet of Things with Fog Computing for an Air Quality Monitoring System

Air Monitoring becomes a systematic approach for sensitivity and finding out the cir-cumstances of the atmosphere. The major concern of air quality monitoring is to meas-ure the concentration of pollution and other important parameter related to the con-tamination and provides information in real-time to make decisions at right time to cure lives and save the environment. This paper proposes an Architectural Framework for the air quality monitoring system based on Internet-of-Things (IoT) and via Fog computing techniques with novel methods to obtain real-time and accurate measurements of con-ventional air quality monitoring. IoT-based real-time air pollution monitoring system is projected to at any location and stores the measured value of various pollutants over a web server with the Internet. It can facilitate the process and filter data near the end of the IoT nodes in a concurrent manner and improving the Latency issue with the quality of services

Smart and Portable Air-Quality Monitoring IoT Low-Cost Devices in Ibarra City, Ecuador

Nowadays, increasing air-pollution levels are a public health concern that affects all living beings, with the most polluting gases being present in urban environments. For this reason, this research presents portable Internet of Things (IoT) environmental monitoring devices that can be installed in vehicles and that send message queuing telemetry transport (MQTT) messages to a server, with a time series database allocated in edge computing. The visualization stage is performed in cloud computing to determine the city air-pollution concentration using three different labels: low, normal, and high. To determine the environmental conditions in Ibarra, Ecuador, a data analysis scheme is used with outlier detection and supervised classification stages. In terms of relevant results, the performance percentage of the IoT nodes used to infer air quality was greater than 90%. In addition, the memory consumption was 14 Kbytes in a flash and 3 Kbytes in a RAM, reducing the power consumption and bandwidth needed in traditional air-pollution measuring stations.Novo Nordisk Foundation NNF20OC0064411Corporacion Ecuatoriana para el Desarrollo de la Investigacion y la Academia (CEDIA), Ecuador CEPRA XII-2018-13Universidad de Las Americas (UDLA), Quito, Ecuador IEA.WHP.21.0