The present paper introduces the creation of an algorithm and the software used to determine the energetic performance and monitor the efficiency of hydraulic pumps working in various industrial applications, such as water supply systems, water treatment processes, and irrigation systems, particularly in the cases where there is no permanent monitoring. Our field investigations and the surveyed literature show that the only parameter that is neither monitored nor computed is the efficiency of the pumps. The software implementation allows for determining the in-service efficiency of the pumps and comparing it to the value associated with the best efficiency point (BEP). The solution is user-friendly and can be easily installed on any computer or smartphone. The software has been applied and tested in the Hydraulic Machines Laboratory at the “Politehnica” University Timişoara and at the AQUATIM S.A. regional water supply company. The software module monitors the operating regimes of the pumps and supports the deployment of predictive maintenance and servicing.

Standard log transmission protocols do not offer a robust way of segregating the log network from potential threats. A secure log transmission system and the realization of a data diode using affordable components are proposed. Unidirectional data flow prevents unauthorized access and eavesdropping, ensuring the integrity and confidentiality of sensitive log data. The system uses an encryption protocol that requires that the upstream and the downstream of the data diode are perfectly synchronized, mitigating replay attacks. It has been shown that message amplification can mitigate UDP packet loss, but this is only required when the data diode traffic is congested. The implementation of the encryption algorithm is suitable for resource-constrained devices and it has been shown to produce random-looking output even on a reduced number of rounds when compared to the parent cipher. Several improvements have been made to the original encryption algorithm for which an actual implementation was missing. Free software and datasets have been made available to reproduce the results. The complete solution is easy to reproduce in order to secure the segregation of a log network inside any scenario where logging is required by the law and log tampering must be prevented.

The Internet of Things produces vast amounts of data that require specialized algorithms in order to secure them. Lightweight cryptography requires ciphers designed to work on resource-constrained devices like sensors and smart things. A new encryption scheme is introduced based on a blend of the best-performing algorithms, SIMECK and TEA. A selection of software-oriented Addition–Rotation–XOR (ARX) block ciphers are augmented with a dynamic substitution security layer. The performance is compared against other lightweight approaches. The US National Institute of Standards and Technology (NIST) SP800-22 Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications and the German AIS.31 of the Federal Office for Information Security (BSI) are used to validate the output of the proposed encryption scheme. The law of iterated logarithm (LIL) for randomness is verified in all three forms. The total variance (TV), the Hellinger Distance (HD), and the root-mean-square deviation (RMSD) show values smaller than the required limit for 10.000 sequences of ciphertext. The performance evaluation is analyzed on a Raspberry PICO 2040. Several security metrics are compared against other ciphers, like ${\chi }^2$ and encryption quality (EQ). The results show that SIMECK-T is a powerful and fast, software-oriented, lightweight cryptography solution.

This paper presents a simple to use software system for the quick assessment and monitoring of the efficiency of hydraulic generators deployed in drinking water transportation systems. The software has been validated by experimental results at constant speed and provides an easy to use smartphone application for the assessment of the efficiency using in-situ QR code stickers for the pumps in service. The estimated flow is confirmed with 3% accuracy compared against the experimental data.