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1. A Blockchain-based Traceability System for Waste Management in Smart Cities

   Gopalakrishnan, Praveen Kumare ; Hall, John ; Behdad, Sara ( August 2020 , the ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2020, August 16 – 19, 2020, St. Louis, MO)

   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. 

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2. A stochastic optimization framework for planning of waste collection and value recovery operations in smart and sustainable cities

   https://doi.org/https://doi.org/10.1016/j.wasman.2018.05.019  

   Jatinkumar Shah, Parth ; Anagnostopoulos, Theodoros ; Zaslavsky, Arkady ; Behdad, Sara ( August 2018 , Waste management)

   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. 

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3. Moving towards Real-time Data-driven Quality Monitoring: A Case Study of Hard Disk Drives

   Raihanian Mashhadi, Ardeshir ; Cade, Willie ; Behdad, Sara ( August 2018 , Procedia Manufacturing, SME North American Manufacturing Research Conference)

   Since its emergence, the cloud manufacturing concept has been transforming the manufacturing and remanufacturing industry into a big data and service-oriented environment. The aggressive push toward data collection in cloud-based and cyber-physical systems provides both challenges and opportunities for predictive analytics. One of the key applications of predictive analytics in such domains is predictive quality management that aims to fully exploit the potentials provided by the enormous data collected via cloud-based systems. As a case study, a data set of hard disk drives’ Self-Monitoring, Analysis and Reporting Technology (SMART) attributes from a cloud-storage service provider has been analyzed to derive some insights about the challenges and opportunities of using product lifecycle data. An analysis of time-to-failure monitoring of hard disk drives in real-time has been carried out and the corresponding challenges have been discussed. 

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4. A Latency-Defined Edge Node Placement Scheme for Opportunistic Smart Cities

   https://doi.org/10.1109/PerComWorkshops51409.2021.9430977  

   Madamori, Oluwashina ; Max-Onakpoya, Esther ; Erhardt, Gregory D. ; Baker, Corey E. ( January 2021 , 2021 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops))

   null (Ed.)

   Smart city projects have the potential to improve the management of environmental and public infrastructure. However, the operational and capital expenditures of smart cities can prevent cities from becoming smarter. A notable factor that influences the cost is providing cellular Internet connectivity to IoT devices. 5G has been proposed as a possible solution, but projections show that 5G will not be able to support the load of billions of IoT devices coming online. To mitigate this, people, vehicles, and other nodes in transportation networks can be exploited to transmit non-urgent data by leveraging device-to-device communication in order to reduce cellular connectivity costs associated with smart city sensors. Hence, this paper addresses cost-effective edge node placement in smart cities that opportunistically leverage public transit networks. We introduce an algorithm that selects a set of edge nodes that provide minimal delivery delay within a budget. The algorithm is evaluated for two public transit network data-sets: Chapel Hill, North Carolina and Louisville, Kentucky and results show that our algorithm outperforms betweeness and in-degree centrality metrics with a reduction in latency of over 20 minutes. 

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5. IoT Security and Safety Testing Toolkits for Water Distribution Systems

   https://doi.org/10.1109/IOTSMS53705.2021.9704886  

   O'Toole, Sean ; Sewell, Cameron ; Mehrpouyan, Hoda ( December 2021 , 2021 8th International Conference on Internet of Things: Systems, Management and Security (IOTSMS))

   Due to the critical importance of Industrial Control Systems (ICS) to the operations of cities and countries, research into the security of critical infrastructure has become increasingly relevant and necessary. As a component of both the research and application sides of smart city development, accurate and precise modeling, simulation, and verification are key parts of a robust design and development tools that provide critical assistance in the prevention, detection, and recovery from abnormal behavior in the sensors, controllers, and actuators which make up a modern ICS system. However, while these tools have potential, there is currently a need for helper-tools to assist with their setup and configuration, if they are to be utilized widely. Existing state-of-the-art tools are often technically complex and difficult to customize for any given IoT/ICS processes. This is a serious barrier to entry for most technicians, engineers, researchers, and smart city planners, while slowing down the critical aspects of safety and security verification. To remedy this issue, we take a case study of existing simulation toolkits within the field of water management and expand on existing tools and algorithms with simplistic automated retrieval functionality using a much more in-depth and usable customization interface to accelerate simulation scenario design and implementation, allowing for customization of the cyber-physical network infrastructure and cyber attack scenarios. We additionally provide a novel in tool assessment of network’s resilience according to graph theory path diversity. Further, we lay out a roadmap for future development and application of the proposed tool, including expansions on resiliency and potential vulnerability model checking, and discuss applications of our work to other fields relevant to the design and operation of smart cities. 

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