• A scalable and cost-effective IoT-based noise monitoring system is developed for smart urban environments. • The system integrates low-cost acoustic sensors, edge-based CNN noise classification, and a web interface for data visualization. • The proposed model, using Mel Spectrogram and MobileNet, achieves a 90.18 % classification accuracy. • The deployed system demonstrates low latency, with 0.37 s transmission delay and 2.5 s processing time on a Raspberry Pi. Increasing noise pollution in urban areas underscores the need for an autonomous system to monitor and control noise. Beyond detecting noise levels, identifying noise sources further improves noise management. This work presents a scalable IoT-based sensing platform for smart environment applications. The system integrates low-cost devices for acoustic measurement, edge devices to enable noise source identification, a back-end infrastructure crucial for efficient acoustic data and device management, and a web-based application facilitating noise data visualization. Our study explores three feature extraction techniques and eight Convolutional Neural Network (CNN)-based pre-trained models for noise classification on the resource-constrained Raspberry Pi platform and compares their performance. Leveraging pre-trained models helps speed up the model development process. UrbanSound8k, ESC-50 datasets, and audio data collected with our low-cost microphone are used for model development and validation. The evaluation results show that our hierarchical model, utilizing the Mel Spectrogram feature extraction method and a MobileNet model, achieves the highest accuracy of 90.18 %. Furthermore, we deploy the system and assess its performance. Our system can reliably transmit audio data with an average delay of 0.37 s, and the Raspberry Pi can perform feature extraction and classification within an average of 2.5 s. Hence, our solution offers a comprehensive and cost-effective solution to enhance noise management and control.

Web servers play a crucial role in web technology. Insufficient protection can lead to serious risks, such as sensitive data exposure. To reduce risk of successful attacks, regular web server configuration audits are conducted. However, manual auditing is often tedious and error-prone, as it requires running commands to check configurations. To enhance this process, we introduce CASA, an automated audit tool designed for four widely used web servers: Nginx, Apache HTTP, Apache Tomcat, and Microsoft IIS. CASA evaluates configurations against industry standard CIS benchmarks, identifies non-compliant settings, and generates HTML audit reports. Our analysis shows that CASA significantly enhances automation in security auditing. We validate its effectiveness by comparing results with manual audits and analysing default and publicly available configurations from GitHub. The findings indicate low compliance with security benchmarks, with less than half of configurations meeting recommended standards, exposing critical risks in unmodified deployments.

Wireless sensor-actuator networks (WSANs) are gaining momentum in industrial process automation as a communication infrastructure for lowering deployment and maintenance costs. In traditional wireless control systems, the plant controller and the network manager operate in isolation, which ignores the significant influence of network reliability on plant control performance. To enhance the dependability of industrial wireless control, we propose a holistic cyber-physical management framework that employs runtime coordination between the plant control and network management. Our design includes a holistic controller that generates actuation signals to physical plants and reconfigures the WSAN to maintain the desired control performance while saving wireless resources. As a concrete example of holistic control, we design a holistic manager that dynamically reconfigures the number of transmissions in the WSAN based on online observations of physical and cyber variables. We have implemented the holistic management framework in the wireless cyber-physicalsimulator (WCPS). A systematic case study is presented based on two five-state plants and a load positioning system using a 16-node WSAN. Simulation results show that the holistic management design has significantly enhanced the dependability of the system against both wireless interferences and physical disturbances, while effectively reducing the number of wireless transmissions.

Wireless Sensor-Actuator Networks (WSANs) are being adopted as an enabling technology for Industrial Internet of Things (IIoT) in process industries. Industrial applications impose stringent requirements in reliability and real-time performance on WSANs. To enhance reliability, industrial standards, such as WirelessHART, embrace Time Slotted Channel Hopping (TSCH) that integrates channel hopping and TDMA at the MAC layer. Within a network governed by a same gateway, WirelessHART prohibits channel reuse, i.e., concurrent transmissions in the same channel, to avoid interference between concurrent transmissions. Preventing channel reuse however negatively affects real-time performance. To meet the demand for both reliability and real-time performance by industrial applications, we propose a conservative channel reuse approach designed to enhance the real-time performance while limiting its impact on reliability in WSANs. In contrast to traditional channel reuse designed to optimize performance at the cost of reliability, our conservative approach introduces channel reuse only when needed to meet the timing constraints of flows. Finally, we present an algorithm to detect reliability degradation caused by channel reuse so that channels can be reassigned to further improve reliability. Experimental results based on two physical testbeds show that our approach significantly improves real-time performance while maintaining a high degree of reliability.

Industrial automation has emerged as an important application of wireless sensor-actuator networks (WSANs). To meet stringent reliability requirements of industrial applications, industrial standards such as WirelessHART adopt Time Slotted Channel Hopping (TSCH) as its MAC protocol. Since every link hops through all the channels used in TSCH, a straightforward policy to ensure reliability is to retain a link in the network topology only if it is reliable in all channels used. However, this policy has surprising side effects. While using more channels may enhance reliability due to channel diversity, more channels may also reduce the number of links and route diversity in the network topology. We empirically analyze the impact of channel selection on network topology, routing, and scheduling on a 52-node WSAN testbed. We observe inherent tradeoff between channel diversity and route diversity in channel selection, where using an excessive number of channels may negatively impact routing and scheduling. We propose novel channel and link selection strategies to improve route diversity and network schedulability. Experimental results on two different testbeds show that our algorithms can drastically improve routing and scheduling of industrial WSANs.

Wireless sensor–actuator networks (WSANs) offer an appealing communication technology for process automation applications to incorporate the Internet of Things (IoT). In contrast to other IoT applications, process automation poses unique challenges for industrial WSAN due to its critical demands on reliable and real-time communication. While industrial WSANs have received increasing attention in the research community recently, most published results to date have focused on the theoretical aspects and were evaluated based on simulations. There is a critical need for experimental research on this important class of WSANs. We developed an experimental testbed by implementing several key network protocols of WirelessHART, an open standard for WSANs that has been widely adopted in the process industries based on the HART. We then performed a series of empirical studies showing that graph routing leads to significant improvement over source routing in terms of worst-case reliability, but at the cost of longer latency and higher energy consumption. It is therefore important to employ graph routing algorithms specifically designed to optimize latency and energy efficiency. Our studies also suggest that channel hopping can mitigate the burstiness of transmission failures; a larger channel distance can reduce consecutive transmission failures over links sharing a common receiver. Based on these insights, we developed a novel channel hopping algorithm that utilizes far away channels for transmissions. Furthermore, it prevents links sharing the same destination from using channels with strong correlations. Our experimental results demonstrate that our algorithm can significantly improve network reliability and energy efficiency.

With recent adoption of wireless sensor-actuator networks (WSANs) in industrial automation, industrial wireless control systems have emerged as a frontier of cyber-physical systems. Despite their success in industrial monitoring applications, existing WSAN technologies face significant challenges in supporting control systems due to their lack of real-time performance and dynamic wireless conditions in industrial plants. This article reviews a series of recent advances in real-time WSANs for industrial control systems: 1) real-time scheduling algorithms and analyses for WSANs; 2) implementation and experimentation of industrial WSAN protocols; 3) cyber-physical codesign of wireless control systems that integrate wireless and control designs; and 4) a wireless cyber-physical simulator for codesign and evaluation of wireless control systems. This article concludes by highlighting research directions in industrial cyber-physical systems.

Wireless sensor-actuator networks are gaining ground as the communication infrastructure for process monitoring and control. Industrial applications demand a high degree of reliability and real-time guarantees in communication. Because wireless communication is susceptible to transmission failures in industrial environments, industrial wireless standards such as WirelessHART adopt reliable graph routing to handle transmission failures through retransmissions and route diversity. While these mechanisms are critical for reliable communication, they introduce substantial challenges in analyzing the schedulability of real-time flows. This paper presents the first worst-case end-to-end delay analysis for periodic real-time flows under reliable graph routing. The proposed analysis can be used to quickly assess the schedulability of real-time flows with stringent requirements on both reliability and latency. We have evaluated our schedulability analysis against experimental results on a wireless testbed of 69 nodes as well as simulations. Both experimental results and simulations show that our delay bounds are safe and enable effective schedulability tests under reliable graph routing.

Industry is adopting Wireless Sensor-Actuator Networks (WSANs) as the communication infrastructure for process control applications. To meet the stringent real-time performance requirements of control systems, there is a critical need for fast end-to-end delay analysis for real-time flows that can be used for online admission control. This paper presents a new end-to-end delay analysis for periodic flows whose transmissions are scheduled based on the Earliest Deadline First (EDF) policy. Our analysis comprises novel techniques to bound the communication delays caused by channel contention and transmission conflicts in a WSAN. Furthermore, we propose a technique to reduce the pessimism in admission control by iteratively tightening the delay bounds for flows with short deadlines. Experiments on a WSAN testbed and simulations demonstrate the effectiveness of our analysis for online admission control of real-time flows.