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1. 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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2. Towards a Heterogeneous Internet-of-Things Testbed via Mesh inside a Mesh: Poster Abstract

   https://doi.org/10.1145/2994551.2996710  

   Miao, Luwen; Liu, Kaikai (January 2016, SenSys '16 Proceedings of the 14th ACM Conference on Embedded Network Sensor Systems)

   Connectivity is at the heart of the future Internet-of-Things (IoT) infrastructure, which can control and communicate with remote sensors and actuators for the beacons, data collections, and forwarding nodes. Existing sensor network solutions cannot solve the bottleneck problems near the sink node; the tree-based Internet architecture has the single point of failure. To solve current deficiencies in multi-hop mesh network and cross-domain network design, we propose a mesh inside a mesh IoT network architecture. Our designed "edge router" incorporates these two mesh networks together and performs seamlessly transmission of multi-standard packets. The proposed IoT testbed interoperates with existing multi-standards (Wi-Fi, 6LoWPAN) and segments of networks, and provides both high-throughput Internet and resilient sensor coverage throughout the community. 

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3. IoT-enabled Knowledge Extraction and Edge Device Sustainability in Smart Cities

   https://doi.org/10.1109/SMARTCOMP50058.2020.00060  

   Sikeridis, Dimitrios (September 2020, 2020 IEEE International Conference on Smart Computing (SMARTCOMP))

   Internet of Things (IoT) deployments are becoming the backbone of all future Smart City (SC) environments. They can, therefore, act as massive crowd-sourced data aggregators, driven by device-to-device interactions with SC users' mobile devices and their wireless interfaces. Provided that, our research focuses on developing probabilistic and machine learning models to (a) enable knowledge discovery from passive user interactions with the wireless IoT infrastructure and (b) apply the collected intelligence to increase the energy-efficiency and resiliency of the Smart City's IoT network. In this extended abstract we elaborate on the motivation behind our work, and the related challenges, while pointing to the solutions developed so far. 

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4. A Decentralized Approach For Real Time Anomaly Detection In Transportation Networks

   https://doi.org/10.1109/SMARTCOMP.2019.00063  

   Wilbur, Michael; Dubey, Abhishek; Bruno, Leao; Bhattacharjee, Shameek. (June 2019, 2019 IEEE International Conference on Smart Computing (SMARTCOMP))

   Internet of Things (IoT), edge/fog computing, and the cloud are fueling rapid development in smart connected cities. Given the increasing rate of urbanization, the advancement of these technologies is a critical component of mitigating demand on already constrained transportation resources. Smart transportation systems are most effectively implemented as a decentralized network, in which traffic sensors send data to small low-powered devices called Roadside Units (RSUs). These RSUs host various computation and networking services. Data driven applications such as optimal routing require precise real-time data, however, data-driven approaches are susceptible to data integrity attacks. Therefore we propose a multi-tiered anomaly detection framework which utilizes spare processing capabilities of the distributed RSU network in combination with the cloud for fast, real-time detection. In this paper we present a novel real time anomaly detection framework. Additionally, we focus on implementation of our framework in smart-city transportation systems by providing a constrained clustering algorithm for RSU placement throughout the network. Extensive experimental validation using traffic data from Nashville, TN demonstrates that the proposed methods significantly reduce computation requirements while maintaining similar performance to current state of the art anomaly detection methods. 

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5. Blockchain-Enabled Communication Framework for Secure and Scalable Healthcare Data Processing

   https://doi.org/10.1109/SoutheastCon56624.2025.10971535  

   Das, Debashis; Landrum, La Chiara; Chatterjee, Pushpita; Ghosh, Uttam; Hussain, Sajid (March 2025, IEEE)

   The need for secure and efficient communication between connected devices continues to grow in healthcare systems within smart cities. Secure communication of healthcare data in Internet of Things (IoT) systems is critical to ensure patient privacy and data integrity. Problems with healthcare communication, like data breaches, integrity issues, scalability issues, and cyber threats, make it harder for people to trust doctors, cause costs to rise, stop people from using new technology, and put private data at risk. So, this paper presents a blockchain-based hybrid method for sending secure healthcare data that combines IoT systems with blockchain technology and high-tech encryption techniques like elliptic curve cryptography (ECC). The proposed method uses the public key of a smart contract to encrypt private data to protect its privacy. It also uses cryptographic hashing and digital signatures to make sure that the data is correct and real. The framework stores metadata (e.g., hashes and signatures) on-chain, and large data uses off-chain storage like IPFS to reduce costs and improve scalability. It also incorporates a mechanism to authenticate IoT devices and enable secure communication across heterogeneous networks. Moreover, this work bridges gaps in existing solutions by providing an end-to-end secure communication system for healthcare applications. It provides strong data security and efficient storage for a reliable and scalable way to handle healthcare data safely in IoT ecosystems. 

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