Smart Me versus Smart Things: The Development of a Personal Resource Planning (PRP) System through Human Interactions with Data Enabled by the IoT

智能我与智能物：通过人机交互与物联网支持的数据开发个人资源规划 (PRP) 系统

• 批准号: EP/L023911/1
• 负责人: Irene Ng
• 金额: $ 49.09万
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2014
• 资助国家: 英国
• 起止时间: 2014 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FL023911%2F1
• 关键词: Smart; Me; versus; Things; Development

Every day we see the development of new "smart" things and come closer and closer to the moment when the perfect "smart" home of the future becomes a reality. A "Smart" home, is one in which each appliance (thing) is not only controllable but is also "intelligent", ie. tailored to our individual needs. Yet, smart objects and smart homes often consider the individual as a passive entity to be 'served', rather than an empowered individual who can make smart decisions based on information. This is often because of the assumption that human cognition isn't able to take on the massive amount of information that could be generated from such smart objects. Indeed, very little is known about how people interact with data and how much of the data which we generate can actually inform our day-to-day decision making. We also do not know whether data generated within a home can change our consumption habits and behaviour. Finally, we are uncertain about whether and to what extent the data that we produce influences other decision makers in our household. Our project offers a new approach to answering these questions by observing actual household behaviour "in the wild" and developing a personal resource planning system (PRP) to support decisions made by individuals, ie. a smart 'me'. Our approach is different from existing IoT research in the following ways. First, while traditional research views the customer, who either accepts or rejects the product/service developed by businesses, to be outside the supply system, our approach offers a new perspective in which the customer is also viewed as an inside component of the supply system. This means that the customer, through his/her behaviour, becomes an inherent component of the supply system, and thereby transforms this system into a collaborative exchange system. This collaborative exchange system allows customers to interact with businesses and make decisions about how much customisation they would like to see in each product/service they themselves consume (e.g., Crowcroft et al., 2011; McAuley et al., 2011; Ng. et al., 2013). Second, since our approach has a person (customer) in the centre, the main focus of this project is to understand how "smart" things interact with human behaviour, and possibly how this behaviour can be informed by the new data from "smart" things to catalyse the appearance of a more informed "smart" consumer (e.g., Ng, 2012). Finally, our third contribution to existing research is to create data architecture through the IoT which would allow customers to make more informed "smart" decisions. In a way, the main output of this project will be a proof of concept that customers could be "nudged" into making "smarter" consumption decisions which would optimise business-customer interactions and create more value for each household.

每一天，我们都能看到新的“智能”事物的发展，并越来越接近未来完美的“智能”家居成为现实的那一刻。“智能”家居，是指每个家用电器(东西)不仅是可控的，而且是“智能的”，即。为我们的个人需求量身定做。然而，智能物品和智能家居往往将个人视为一个被动的实体，而不是一个能够根据信息做出明智决定的授权个人。这通常是因为人们认为，人类的认知能力无法承受这些智能物体所产生的海量信息。事实上，关于人们如何与数据交互，以及我们产生的数据中有多少实际上可以为我们的日常决策提供信息，人们知之甚少。我们也不知道家里产生的数据是否会改变我们的消费习惯和行为。最后，我们不确定我们产生的数据是否会影响我们家庭中的其他决策者，以及影响程度有多大。我们的项目提供了一种新的方法来回答这些问题，通过观察实际的家庭行为“在野外”和开发一个个人资源规划系统(PRP)，以支持个人作出的决定，即。一个聪明的“我”。我们的方法与现有的物联网研究有以下不同之处。首先，传统的研究认为，接受或拒绝企业开发的产品/服务的客户处于供应系统之外，而我们的方法提供了一个新的视角，即客户也被视为供应系统的内部组成部分。这意味着客户通过他/她的行为成为供应系统的固有组成部分，从而将该系统转变为协作交换系统。这种协作交换系统允许客户与企业互动，并决定他们希望在自己消费的每个产品/服务中看到多少定制(例如，Crowcroft等人，2011年；McAuley等人，2011年；Ng。等人，2013年)。其次，由于我们的方法以人(客户)为中心，本项目的主要重点是了解“智能”事物如何与人类行为互动，以及可能如何通过来自“智能”事物的新数据来告知这种行为，以促进更知情的“智能”消费者的出现(例如，Ng，2012)。最后，我们对现有研究的第三个贡献是通过物联网创建数据架构，使客户能够做出更明智的决策。在某种程度上，这个项目的主要成果将是一个概念的证明，即客户可以被“推动”做出“更明智的”消费决定，这将优化企业与客户的互动，并为每个家庭创造更多价值。

项目成果

Clustering Big Urban Data Sets

聚类大城市数据集

• 发表时间: 2015
• 作者: Al Shami, A.

Fuzzy partition technique for clustering Big Urban dataset

• DOI: 10.1109/sai.2016.7555984
• 发表时间: 2016-07
• 期刊: 2016 SAI Computing Conference (SAI)
• 作者: Ahmad Alshami;Weisi Guo;Ganna Pogrebna

Understanding Happiness in Cities using Twitter: Jobs, Children, and Transport

使用 Twitter 了解城市的幸福感：工作、儿童和交通

• 发表时间: 2016
• 作者: Guo W

Servitization through Human-data Interaction: a Behavioural Approach

通过人与数据交互的服务化：行为方法

• 发表时间: 2015
• 作者: Pogrebna G

Multi-Sided Markets and Pricing for Big Personal Data: Smarter Cities and Citizens

大个人数据的多边市场和定价：智慧城市和公民

• 发表时间: 2015
• 作者: Pogrebna G