The objective of precision beekeeping is to minimize resource consumption and maximize productivity of bees. This is achieved by detecting and predicting beehive states by monitoring apiary and beehive related parameters like temperature, weight, humidity, noise, vibrations, air pollution, wind, precipitation, etc. These parameters are collected as a raw input data by use of multiple different sensory devices, and are often imperfect and require creation of correlation between time data series. Currently, most researches focus on monitoring and processing each parameter separately, whereas combination of multiple parameters produces information that is more sophisticated. Raw input data sets that complement one another could be pre-processed by applying data fusion methods to achieve understanding about global research subject. There are multiple data fusion methods and classification models, distinguished by raw input data type or device usage, whereas sensor related data fusion is called sensor fusion. This paper analyses existing data fusion methods and process in order to identify data fusion challenges and correlate them with precision beekeeping objectives. The research was conducted over a period of 5 months, starting from October, 2019 and was based on analysis and synthesis of scientific literature. The conclusion was made that requirement of data fusion appliance in precision beekeeping is determined by a global research objective, whereas input data introduces main challenges of data and sensor fusion, as its attributes correlate with potential result.

In conditions where induction motors are frequently started, overloaded and used in high inertia applications with long starting times, supplied from frequency converter, a temperature protection system are more reliable to protect induction motor stator winding against thermal overloads. There are different types of temperature protections - thermostat, PTC thermistor, resistance temperature detector (RTD) and thermocouples, so it is important to know the properties of each type to choose an adequate protection system. Analyses of temperature sensor properties and their advantages and disadvantages show, that PTC thermistor is a cost-effective temperature protection solution, but for medium and high voltage induction motor protection RTD are commonly used. A virtual model has been represented to simulate the temperature sensor thermal time constant under different thermal conductivity and thickness of winding magnet wire insulation.

Monitoring the operation of car engines using a smartphone and cloud services is a concept that falls within the field of intelligent vehicle technologies. Using information collection system, vehicle fleet companies can effectively manage the usage of their vehicles, minimizing investment and maintenance costs, preventing accidents and failures, identifying poor driving behaviour among employees, and reducing expenses associated with fuel, tires, and other resources. This approach involves collecting real-time data from the vehicle engine sensors, transferring data to the cloud via a smartphone, and then using cloud services to analyse and manage the information, making it understandable in a simple way. This review reflects on the working efficiency of internal combustion engines and the reduction of pollution to the environment, also gathers existing literature to gain insights into vehicle sensor data acquisition technology and systems in the automotive industry identifying gaps in current knowledge and provide a conceptual framework for next practical research in this field. After explaining the general idea of logistics tasks in technology development, various sensors and their methods are associated with engine properties are introduced. The research results show that most articles are about data acquisition systems from different systems. They can provide convenience and flexibility for users, allowing them to easily access and adjust settings on-the-go, enabling real-time monitoring and adjustment of engine performance, helping users optimize efficiency and performance based on their specific needs and preferences.

Engineering structures such as bridges, overpasses, and viaducts constitute a crucial component of the infrastructure of any industrial city. The wide-scale industrialisation of the twentieth century transformed the urban landscape. Many designs and solutions have become morally and physically outdated since those times, yet their usage continues, which is not always safe. With the aging of infrastructure, the issue of their further safe use inevitably arises. Geodetic monitoring of structural deformations can provide control and safety, as well as gather data for designers and engineers. The data collected by deformation monitoring systems should form the basis for the reconstruction and maintenance project of infrastructural facilities. Deformation monitoring systems are designed for each object based on the parameters of the structure, taking into account the constructive features, materials, and the importance of the infrastructural object to the city traffic. It is not always possible to completely close an overpass during reconstruction, as this would affect the transport flow in a specific district of the city. Monitoring of recently put into operation structures will ensure the collection of deformation data for the survival analysis. Once the structural health is defined, the period of service life until scheduled maintenance will be determined. As a result of our research on the Brasa overpass in Riga, we developed a scheme for swift response to signals from the monitoring systemʼs sensors. Additionally, we ensured the safe operation of the old overpass during the construction of the new one by promptly utilising data obtained from the deformation monitoring system.