Open Access

The number of use cases for autonomous vehicles is increasing day by day especially in commercial applications. One important application of autonomous vehicles can be found within the parcel delivery section. Here, autonomous cars can massively help to reduce delivery efforts and time by supporting the courier actively. One important component of course is the autonomous vehicle itself. Nevertheless, beside the autonomous vehicle, a flexible and secure communication architecture also is a crucial key component impacting the overall performance of such system since it is required to allow continuous interactions between the vehicle and the other components of the system. The communication system must provide a reliable and secure architecture that is still flexible enough to remain practical and to address several use cases. In this paper, a robust communication architecture for such autonomous fleet-based systems is proposed. The architecture provides a reliable communication between different system entities while keeping those communications secure. The architecture uses different technologies such as Bluetooth Low Energy (BLE), cellular networks and Low Power Wide Area Network (LPWAN) to achieve its goals.

With the surge in global data consumption with proliferation of Internet of Things (IoT), remote monitoring and control is increasingly becoming popular with a wide range of applications from emergency response in remote regions to monitoring of environmental parameters. Mesh networks are being employed to alleviate a number of issues associated with single-hop communication such as low area coverage, reliability, range and high energy consumption. Low-power Wireless Personal Area Networks (LoWPANs) are being used to help realize and permeate the applicability of IoT. In this paper, we present the design and test of IEEE 802.15.4-compliant smart IoT nodes with multi-hop routing. We first discuss the features of the software stack and design choices in hardware that resulted in high RF output power and then present field test results of different baseline network topologies in both rural and urban settings to demonstrate the deployability and scalability of our solution.

A systematic toxicological analysis procedure using high-performance thin layer chromatography in combination with fibre optical scanning densitometry for identification of drugs in biological samples is presented. Two examples illustrate the practicability of the technique. First, the identification of a multiple intake of analgesics: codeine, propyphenazone, tramadol, flupirtine and lidocaine, and second, the detection of the sedative diphenhydramine. In both cases, authentic urine specimens were used. The identifications were carried out by an automatic measurement and computer-based comparison of in situ UV spectra with data from a compiled library of reference spectra using the cross-correlation function. The technique allowed a parallel recording of chromatograms and in situ UV spectra in the range of 197–612 nm. Unlike the conventional densitometry, a dependency of UV spectra by concentration of substance in a range of 250–1000 ng/spot was not observed.