Smarter Home Indoor Air Quality Monitoring System

室内空气质量（IAQ）是影响人们舒适、健康和福祉的主要环境风险之一。人们大约90%的时间是在室内度过的，每天接触到的室内空气污染物有时可能比室外污染物高10倍以上（EPA）。例如，据估计，高达20%的人口患有由室内环境中通常存在的物质引起的哮喘和其他过敏性疾病。此外，烟草烟雾、氡、石棉和甲醛等室内污染物可能在很大程度上导致人口中癌症事件的增加。世界卫生组织（世卫组织）估计，每年有70万人死于呼吸不良。显然，室内空气质量对人们的舒适和健康有重大影响。在这个提案中，我们计划开发一个超灵敏的家庭室内空气质量传感系统，该系统可以检测有害的污染水平，预测和识别污染源，并提供可行的建议来帮助人们改善室内空气质量。使用这个新系统将使用户能够将家庭任务与污染事件联系起来，并采取行动减少污染。我们相信这将导致行为的改变和积极的行动，以减少影响他们健康的室内空气质量。新的室内空气质量系统将能够检测和测量特定的、高风险的和常见的有害污染物和微粒，以及室内空气质量和通风的其他指标，包括二氧化碳、环境温度和湿度。我们还将使用机器学习技术来分析传感器数据，以准确预测污染水平的增加，确定潜在原因，并告知预防和缓解措施。室内空气质素系统的设计将符合使用者的要求，并能准确量度污染程度。我们将改进我们的气体传感器阵列平台，以检测关键的常见有害污染物甲醛（<10ppb）和一氧化碳（ppm）。我们的新型污染气体传感器阵列将与商用传感器（二氧化碳、总挥发性有机物（TVOCs）、颗粒传感器、温度和湿度，并具有蓝牙连接）集成在一起，形成一个新的空气室内空气质量系统。

Indoor air quality (IAQ) is one of the leading environmental risks, which affects people's, comfort, health, and well-being. People spend around 90% of their time indoors, and daily exposure to indoor air pollutants may occasionally be more than 10 times higher than outdoor pollutant (EPA). It is estimated, for instance, that up to 20% of the population suffers from asthma and other allergic diseases caused by substances typically present in indoor environments. In addition, indoor pollutants such as tobacco smoke, radon, asbestos and formaldehyde may substantially contribute to the increase of cancer incidents in the population. The World Health Organization (WHO) estimates that 700,000 people per year die from poor breathing conditions. Clearly, IAQ has a significant impact on people's comfort and health.In this proposal, we plan to develop an ultrasensitive home-based IAQ sensing system that can detect adverse levels of pollution, predict and identify the pollution sources, and provide actionable suggestions to help people improve IAQ. Using this new system will enable users to correlate household tasks to pollution events and take action to reduce them. We believe this will lead to a behaviour change and positive action to reduce IAQ that affects their health.The new IAQ system would have the capability to detect and measure specific, high risk and common harmful pollutants and particulates alongside other indicators of IAQ and ventilation including carbon dioxide, ambient temperature and humidity. We would also use machine learning techniques to analyse the sensor data to accurately predict an increase in pollution levels, identify the potential cause and inform prevention and mitigation measures.The IAQ system would be designed to meet the user requirements and to also measure the pollution levels accurately. We would modify our gas sensor array platform to detect key common hazardous pollutants formaldehyde (<10ppb) and carbon monoxide (ppm). Our new pollution gas sensor array would be integrated with commercial sensors, (carbon dioxide, total volatile organics (TVOCs), particulate sensor, temperature and humidity and has Bluetooth connectivity) to make a new air IAQ system.