The rapid growth in the number of vehicles has led to traffic congestion, pollution, and delays in logistic transportation in metropolitan areas. IoT has been an emerging innovation, moving the universe towards automated processes and intelligent management systems. This is a critical contribution to automation and smart civilizations. Effective and reliable congestion management and traffic control help save many precious resources. An IoT-based ITM system set of sensors is embedded in automatic vehicles and intelligent devices to recognize, obtain, and transmit data. Machine learning (ML) is another technique to improve the transport system. The existing transport-management solutions encounter several challenges resulting in traffic congestion, delay, and a high fatality rate. This research work presents the design and implementation of an Adaptive Traffic-management system (ATM) based on ML and IoT. The design of the proposed system is based on three essential entities: vehicle, infrastructure, and events. The design utilizes various scenarios to cover all the possible issues of the transport system. The proposed ATM system also utilizes the machine-learning-based DBSCAN clustering method to detect any accidental anomaly. The proposed ATM model constantly updates traffic signal schedules depending on traffic volume and estimated movements from nearby crossings. It significantly lowers traveling time by gradually moving automobiles across green signals and decreases traffic congestion by generating a better transition. The experiment outcomes reveal that the proposed ATM system significantly outperformed the conventional traffic-management strategy and will be a frontrunner for transportation planning in smart-city-based transport systems. The proposed ATM solution minimizes vehicle waiting times and congestion, reduces road accidents, and improves the overall journey experience.

Wireless sensor networks (WSNs) can be quickly and randomly deployed in any harsh and unattended environment and only authorized users are allowed to access reliable sensor nodes in WSNs with the aid of gateways (GWNs). Secure authentication models among the users, the sensor nodes and GWN are important research issues for ensuring communication security and data privacy in WSNs. In 2013, Xue et al. proposed a temporal-credential-based mutual authentication and key agreement scheme for WSNs. However, in this paper, we point out that Xue et al.’s scheme cannot resist stolen-verifier, insider, off-line password guessing, smart card lost problem and many logged-in users’ attacks and these security weaknesses make the scheme inapplicable to practical WSN applications. To tackle these problems, we suggest a simple countermeasure to prevent proposed attacks while the other merits of Xue et al.’s authentication scheme are left unchanged.

In recent years, with the increase in degenerative diseases and the aging population in advanced countries, demands for medical care of older or solitary people have increased continually in hospitals and healthcare institutions. Applying wireless sensor networks for the IoT-based telemedicine system enables doctors, caregivers or families to monitor patients’ physiological conditions at anytime and anyplace according to the acquired information. However, transmitting physiological data through the Internet concerns the personal privacy of patients. Therefore, before users can access medical care services in IoT-based medical care system, they must be authenticated. Typically, user authentication and data encryption are most critical for securing network communications over a public channel between two or more participants. In 2016, Liu and Chung proposed a bilinear pairing-based password authentication scheme for wireless healthcare sensor networks. They claimed their authentication scheme cannot only secure sensor data transmission, but also resist various well-known security attacks. In this paper, we demonstrate that Liu–Chung’s scheme has some security weaknesses, and we further present an improved secure authentication and data encryption scheme for the IoT-based medical care system, which can provide user anonymity and prevent the security threats of replay and password/sensed data disclosure attacks. Moreover, we modify the authentication process to reduce redundancy in protocol design, and the proposed scheme is more efficient in performance compared with previous related schemes. Finally, the proposed scheme is provably secure in the random oracle model under ECDHP.