An integrated method for short-term prediction of road traffic conditions for intelligent transportation systems applications

The paper deals with the short-term prediction of road traffic conditions within Intelligent Transportation Systems applications. First, the problem of traffic modeling and the potential of different traffic monitoring technologies are discussed. Then, an integrated method for short-term traffic prediction is presented, which integrates an Artificial Neural Network predictor that forecasts future states in standard conditions, an anomaly detection module that exploits floating car data to individuate possible occurrences of anomalous traffic conditions, and a macroscopic traffic model that predicts speeds and queue progressions in case of anomalies. Results of offline applications on a primary Italian motorway are presented

Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions

SecuCode: Intrinsic PUF Entangled Secure Wireless Code Dissemination for Computational RFID Devices

The simplicity of deployment and perpetual operation of energy harvesting devices provides a compelling proposition for a new class of edge devices for the Internet of Things. In particular, Computational Radio Frequency Identification (CRFID) devices are an emerging class of battery-free, computational, sensing enhanced devices that harvest all of their energy for operation. Despite wireless connectivity and powering, secure wireless firmware updates remains an open challenge for CRFID devices due to: intermittent powering, limited computational capabilities, and the absence of a supervisory operating system. We present, for the first time, a secure wireless code dissemination (SecuCode) mechanism for CRFIDs by entangling a device intrinsic hardware security primitive Static Random Access Memory Physical Unclonable Function (SRAM PUF) to a firmware update protocol. The design of SecuCode: i) overcomes the resource-constrained and intermittently powered nature of the CRFID devices; ii) is fully compatible with existing communication protocols employed by CRFID devices in particular, ISO-18000-6C protocol; and ii) is built upon a standard and industry compliant firmware compilation and update method realized by extending a recent framework for firmware updates provided by Texas Instruments. We build an end-to-end SecuCode implementation and conduct extensive experiments to demonstrate standards compliance, evaluate performance and security.Comment: Accepted to the IEEE Transactions on Dependable and Secure Computin

VLIT NODE Sensor Technology and Prefarm

Precision farming systems are based on a detailed monitoring of information and data that are necessary for successful decision-making in crop production. The system is designed for data collection from several resources. In past years an extensive research and development work has been done in the field of wireless sensor networks (WSN) in the world. When a wireless sensor network (WSN) is used for agricultural purposes, it has to provide first of all a long-reach signal. The present paper describes new long distance RFID based technology implementation - VLIT NODE.Wireless Sensor Network, Precision Agriculture, RFID., Research and Development/Tech Change/Emerging Technologies, Research Methods/ Statistical Methods, GA, IN,

Improving RFID read rate reliability by a systemic error detection approach

Reliability, security and privacy are the key concerns with RFID (radio frequency identification) adoption. While the mainstream RFID research is focused on solving the security and privacy issues, this paper focuses on addressing the reliability issues in general and detecting read rate failures in particular. We specifically consider the issue of detecting if some RFID tags are not read at all, and if the tags are not read an alarm should be activated. This is quite different from the main stream RFID reliability research which attempts to increase the read rate by developing new and powerful antennas or improving the surrounding environment. To address this issue, we present a novel solution which can detect missed readings and notify appropriate entity to take suitable action against it. The novelty of the proposed solution lies in the combined use of RFID reader along with a normal weighing machine. The concept is to compare the gross weight of the tagged items against the gross weight (of the same items) stored in a backend database. The backed database can only be accessed for those RFID tags which are properly read. If some tags are not read at all these weights would vary and hence incorrect readings could be identified. This paper provides the detailed theoretical foundation for the proposed solution. In addition we compare the proposed solution against existing solutions to demonstrate the success and potential of our solution for practical deployment of RFID in library or supermarket scenario