Green Transportation Choices with IoT and Smart Nudging

Andersen, Anders; Karlsen, Randi; Wei-hai, YU

doi:10.1007/978-3-319-97271-8_13

Cited by 9 publications

(13 citation statements)

References 28 publications

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“…Accuracy in electrical billing is highly needed, especially with the widespread use of smart-home appliances in the daily lives. The development of automatic meter reading (AMR) avoids the need for a person to visit a physical location for reading the meter and reduces the possibility of reading the data wrongly [44]. Currently, General Packet Radio Service (GPRS) solutions are used in this context, but they are quite expensive and can lose SMS packets.…”

Section: Energymentioning

confidence: 99%

A Comprehensive Study of the Use of LoRa in the Development of Smart Cities

Andrade

Yoo

2019

Applied Sciences

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The New Urban Agenda (Agenda 2030) adopted at the United Nations Conference related to Sustainable Urban Development (Habitat III) in the year 2016 has the goal of prompting cities to achieve the identified Sustainable Development Goals by the year 2030. In this context, cities can experiment strategies of circular economy for the optimization of resources, waste reduction, reuse, and recycling. The data generated by the components of an Internet of Things (IoT) ecosystem can contribute in two relevant ways to a smart city model: (1) by the generation of a circular economy and (2) by the creation of intelligence to improve the decision-making processes by citizens or city managers. In this context, it is in our interest to understand the most relevant axes of the research related to IoT, particularly those based on the LoRa technology. LoRa has attracted the interest of researchers because it is an open standard and contributes to the development of sustainable smart cities, since they are linked to the concepts of a circular economy. Additionally, the intention of this work is to identify the technological or practical barriers that hamper the development of solutions, find possible future trends that could exist in the context of smart cities and IoT, and understand how they could be exploited by the industry and academy.

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Section: Energymentioning

confidence: 99%

A Comprehensive Study of the Use of LoRa in the Development of Smart Cities

Andrade

Yoo

2019

Applied Sciences

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“…In [7], we discussed personalization in the context of nudging. A smart nudging system uses personalization and context-awareness to design nudges that are relevant to the current situation of the user.…”

Section: User Profile Learningmentioning

confidence: 99%

“…As we discussed in [7], the nudging system collects data that are historical, current, and represent plans and predictions. Historical data describe the past.…”

Section: Information Collection and Analysismentioning

confidence: 99%

“…Predictions are data trying to guess the future, often based on historical data, current data, and plans. Examples of historical data, current data, plans, and predictions are found in Table 3 [7]. Table 3.…”

Section: Information Collection and Analysismentioning

confidence: 99%

“…Table 3. Examples of historical data, current data, plans and predictions (from [7]). Nudging information may come from sources such as IoT sensors, body sensors, online services, crowdsourcing, and crowdsensing.…”

Section: Information Collection and Analysismentioning

confidence: 99%

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Recommendations with a Nudge

Karlsen

Andersen

2019

Technologies

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In areas such as health, environment, and energy consumption, there is a need to do better. A common goal in society is to get people to behave in ways that are sustainable for the environment or support a healthier lifestyle. Nudging is a term known from economics and political theory, for influencing decisions and behavior using suggestions, positive reinforcement, and other non-coercive means. With the extensive use of digital devices, nudging within a digital environment (known as digital nudging) has great potential. We introduce smart nudging, where the guidance of user behavior is presented through digital nudges tailored to be relevant to the current situation of each individual user. The ethics of smart nudging and the transparency of nudging is also discussed. We see a smart nudge as a recommendation to the user, followed by information that both motivates and helps the user choose the suggested behavior. This paper describes such nudgy recommendations, the design of a smart nudge, and an architecture for a smart nudging system. We compare smart nudging to traditional models for recommender systems, and we describe and discuss tools (or approaches) for nudge design. We discuss the challenges of designing personalized smart nudges that evolve and adapt according to the user’s reactions to the previous nudging and possible behavioral change of the user.

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