The purpose of this paper is to address current issues in industrial robotics applications and to address also the current trends occurring in the industry regarding smaller mobile units in factory and external manufacturing processes relating to the battery powering of robotics devices. Specifically, we shall concentrate the efforts herein on “Mobile Industrial Robotics”. The paper touches briefly on problems associated with both definitions of industrial robots and problems associated with power supply sources of mobile industrial robotics and provides an outline of future work with appropriate solution for smaller mobile industrial mobile units operating in the variable input range of 24V to 48v and outputs in the range of 3.3V to 12V @ 20A in three stages. The project required a fast, turn-key solution which did not allow for a “design from scratch” solution and so detailed herein is suitable design produced in other sectors and relating the details, design process, modelling and examination of a successful and efficient high current DC to DC switch mode power supply. Parameters have been adjusted to our own preferences in the design considerations regarding “Industrial Service Hybrids”  (ISH)1. Other design issues are under assessment and shall be included as the project moves forward.
Flax is cultivated on small areas in Latvia. Flax gives dual-purpose production – fibre and seeds. Latvian flax has a high fibre and seed quality. The quantity of flax fibre and seed yield depends on many factors. Several qualitative and quantitative traits, such as technical stem length, resistance to lodging, vegetation period, yield of straw and seeds, fibre and oil content and quality were evaluated. For the further development of Latvian economy flax varieties and hybrids of Latvian origin are an important goal. Fibre flax varieties 'Blue di Riga', 'Priekuļu 665', 'Ošupes 30' and breeding lines 'S-64-17-93' and 'L11-11/11-94' are valuable material containing a qualitative and quantitative indicators of variety. 92 Latvian accessions of flax hybrids have been evaluated, and 12 accessions with the best seed and straw yield have been selected for further DNA analysis. This will simplify and accelerate the selection of new valuable hybrids that will provide particular advantages in agriculture. The genetic analysis of DNA determines the kinship and diversity of flax varieties and breeding lines which can be used further in flax breeding.
During the honey bee colony's life cycle different colony states can be observed. At certain situations some of the states can negatively impact colony's development (broodless state, swarming) resulting in possible colony's death and increase of beekeepers costs. On the other hand, when honey bee colony is in active brood rearing stage (at the preferable period) it is a sign that the colony is capable of reproduction. By knowing in which state the bee colony are at a specific moment, without opening the hive, beekeeper can improve his apiary management, e.g., timely prepare for further actions. Within the “Application of Information Technologies in Precision Apiculture” (ITAPIC) project, colony monitoring was performed using one temperature sensor per honey bee hive. This gives enough data to examine temperature dynamics and allows to determine the patterns of the given honey bee colony states. Based on these data, it is possible to develop a honey bee colony state identification process. This can be achieved by inspecting the temperature data and developing algorithms for each honey bee colony state or by applying neural networks. Neural networks are widely used for various tasks, including tasks related to classification and data processing. In this paper authors propose a method for honey bee colony state (commencement of brood rearing period and swarming) detection using neural networks with supervised learning.
Highly productive dairy cow' ration under intensive production conditions causes the development of subacute rumen acidosis (SARA). In this paper we discuss a reticulo-ruminal long-acting cyber-physical diagnostic system' prototype, which applies Internet of Things (IoT) for monitoring rumen parameters of cows. The new diagnostic system architecture includes, reticulo-ruminal bolus with pH and temperature sensors, a microcontroller, a radio transmitter and a power supply module. The system includes gateways for data collection from boluses, an MQTT (Message Queuing Telemetry Transport) broker, a web server and a database. The diagnostic system' prototype provides timely data on cow health status to the users, so they can evaluate the cow' health status and implement further actions. Therefore, the use of diagnostic system provides opportunity to increase cow productivity, longevity and to save maintenance cost of milk farms. The results of the first stage of the research are discussed in this paper.
In this paper we report a power monitoring system used in the industrial greenhouse. Monitored data is processed in the device and then transferred to secure cloud services, where the data can be further processed, formatted and sent to the server used for data storage and later analysis. The power monitoring system is a part of the project where various parameters are measured in the greenhouse and as a result, could offer guidelines for the more efficient growth of plants  .
Nowadays industrial greenhouses are implementing various Internet of Things (IoT) technologies, allowing to easily integrate sensor technologies with wireless communications and create cloud-based database solutions. For industrial greenhouses, one of an important parameter is irrigation of crop and also crop biomass growth during the day. Paper deals with the development of IoT based weight sensor for continuous weight measurements in an industrial greenhouse environment, practical data analysis, and new algorithm development for measurement precision improvement. Real measurements are described and results of two algorithm application are compared.
Logistics services include a variety of operations, from freight transportation and warehousing, to order placement in distribution channels and delivery to customers. In order to increase the efficiency and responsiveness of the supply chain, a digital transformation is being carried out, which includes the business model changes and the introduction of various digital technologies in the planning, management and administration of logistics operations. One of the disruptive technologies is Augmented Reality (AR). The aim of the article is to provide a conceptual view of the use of AR in the logistics and supply chain.
The Internet of Things (IoT) will play a significant role in the future market of services. Services require payments. Payments must be confirmed as fast as possible to protect customers and merchants. Integration of IoT to peer-to-peer networks provides a need for choosing an appropriate consensus mechanism and other ways to make transactions faster without losing the required level of security. As security of modern blockchain projects is controlled by decentralized applications like smart contracts, reviewed protocols are supporting this technology.
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