The potential of smart cities in remediating environmental problems in general and waste management, in particular, is an important question that needs to be investigated in academic research. Built on an integrative review of the literature, this study offers insights into the potential of smart cities and connected communities in facilitating waste management efforts. Shortcomings of existing waste management practices are highlighted and a conceptual framework for a centralized waste management system is proposed, where three interconnected elements are discussed: (1) an infrastructure for proper collection of product lifecycle data to facilitate full visibility throughout the entire lifespan of a product, (2) a set of new business models relied on product lifecycle data to prevent waste generation, and (3) an intelligent sensor-based infrastructure for proper upstream waste separation and on-time collection. The proposed framework highlights the value of product lifecycle data in reducing waste and enhancing waste recovery and the need for connecting waste management practices to the whole product lifecycle.
An example of the use of tracking and data sharing technologies for investigating the waste management issues has been discussed. Finally, the success factors for implementing the proposed framework and some thoughts on future research directions have been discussed.
more »
« less
A stochastic optimization framework for planning of waste collection and value recovery operations in smart and sustainable cities
The concept of City 2.0 or smart city is offering new opportunities for handling waste management practices. The existing studies have started addressing waste management problems in smart cities mainly by focusing on the design of new sensor-based Internet of Things (IoT) technologies, and optimizing the routes for waste collection trucks with the aim of minimizing operational costs, energy consumption and transportation pollution emissions. In this study, the importance of value recovery from trash bins is highlighted. A stochastic optimization model based on chance-constrained programming is developed to optimize the planning of waste collection operations. The objective of the proposed optimization model is to minimize the total transportation cost while maximizing the recovery of value still embedded in waste bins. The value of collected waste is modeled as an uncertain parameter to reflect the uncertain value that can be recovered from each trash bin due to the uncertain condition and quality of waste. The application of the proposed model is shown by using a numerical example. The study opens new venues for incorporating the value recovery aspect into waste collection planning and development of new data acquisition technologies that enable municipalities to monitor the mix of recyclables embedded in individual trash bins.
more »
« less
- Award ID(s):
- 1705621
- NSF-PAR ID:
- 10065239
- Date Published:
- Journal Name:
- Waste management
- Volume:
- 78
- ISSN:
- 0956-053X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Urban anomalies have a large impact on passengers' travel behavior and city infrastructures, which can cause uncertainty on travel time estimation. Understanding the impact of urban anomalies on travel time is of great value for various applications such as urban planning, human mobility studies and navigation systems. Most existing studies on travel time have been focused on the total riding time between two locations on an individual transportation modality. However, passengers often take different modes of transportation, e.g., taxis, subways, buses or private vehicles, and a significant portion of the travel time is spent in the uncertain waiting. In this paper, we study the fine-grained travel time patterns in multiple transportation systems under the impact of urban anomalies. Specifically, (i) we investigate implicit components, including waiting and riding time, in multiple transportation systems; (ii) we measure the impact of real-world anomalies on travel time components; (iii) we design a learning-based model for travel time component prediction with anomalies. Different from existing studies, we implement and evaluate our measurement framework on multiple data sources including four city-scale transportation systems, which are (i) a 14-thousand taxicab network, (ii) a 13-thousand bus network, (iii) a 10-thousand private vehicle network, and (iv) an automatic fare collection system for a public transit network (i.e., subway and bus) with 5 million smart cards.more » « less
-
Waste tracking is becoming an important concern for developed countries as well as developing regions, where municipalities aim to assure proper waste management considering environmental and economic objectives. Waste tracking is important not only for a transparent reporting system compatible with environmental regulations but also for economically viable waste collection and recovery solutions. In this paper, a waste tracking system based on the blockchain technology is introduced where different entities involved in the system will be able to retrieve required data from the platform and decide on their level of contributions. The conventional technologies do not provide a sufficient level of transparency and coordination among different entities. With the introduction of blockchain as a tamper-proof technology, municipalities can enhance the efficiency of their waste management efforts. The proposed blockchain technology can connect proper stakeholders towards collaboration and sharing information. The concept of a smart contract for waste management is discussed and further, a decision-making framework is developed to guide users of the system select proper services available to them, depending on the level of data sharing, cost, reliability, and the security level that they expect from the system.more » « less
-
Prototyping and validating hardware–software components, sub-systems and systems within the intelligent transportation system-of-systems framework requires a modular yet flexible and open-access ecosystem. This work presents our attempt to develop such a comprehensive research and education ecosystem, called AutoDRIVE, for synergistically prototyping, simulating and deploying cyber-physical solutions pertaining to autonomous driving as well as smart city management. AutoDRIVE features both software as well as hardware-in-the-loop testing interfaces with openly accessible scaled vehicle and infrastructure components. The ecosystem is compatible with a variety of development frameworks, and supports both single- and multi-agent paradigms through local as well as distributed computing. Most critically, AutoDRIVE is intended to be modularly expandable to explore emergent technologies, and this work highlights various complementary features and capabilities of the proposed ecosystem by demonstrating four such deployment use-cases: (i) autonomous parking using probabilistic robotics approach for mapping, localization, path-planning and control; (ii) behavioral cloning using computer vision and deep imitation learning; (iii) intersection traversal using vehicle-to-vehicle communication and deep reinforcement learning; and (iv) smart city management using vehicle-to-infrastructure communication and internet-of-things.more » « less
-
Abstract Pilot projects have emerged in cities globally as a way to experiment with the utilization of a suite of smart mobility and emerging transportation technologies. Automated vehicles (AVs) have become central tools for such projects as city governments and industry explore the use and impact of this emerging technology. This paper presents a large-scale assessment of AV pilot projects in U.S. cities to understand how pilot projects are being used to examine the risks and benefits of AVs, how cities integrate these potentially transformative technologies into conventional policy and planning, and how and what they are learning about this technology and its future opportunities and risks. Through interviews with planning practitioners and document analysis, we demonstrate that the approaches cities take for AVs differ significantly, and often lack coherent policy goals. Key findings from this research include: (1) a disconnect between the goals of the pilot projects and a city’s transportation goals; (2) cities generally lack a long-term vision for how AVs fit into future mobility systems and how they might help address transportation goals; (3) an overemphasis of non-transportation benefits of AV pilots projects; (4) AV pilot projects exhibit a lack of policy learning and iteration; and (5) cities are not leveraging pilot projects for public benefits. Overall, urban and transportation planners and decision makers show a clear interest to discover how AVs can be used to address transportation challenges in their communities, but our research shows that while AV pilot projects purport to do this, while having numerous outcomes, they have limited value for informing transportation policy and planning questions around AVs. We also find that AV pilot projects, as presently structured, may constrain planners’ ability to re-think transportation systems within the context of rapid technological change.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/https://doi.org/10.1016/j.wasman.2018.05.019
