Large numbers of mobile wireless nodes that can move randomly and join or leave the network at any moment make up mobile ad-hoc networks. A significant number of messages are delivered during information exchange in populated regions because of the Internet of Things' (IoT) exponential increase in connected devices. Congestion can increase transmission latency and packet loss by causing congestion. More network size, increased network traffic, and high mobility that necessitate dynamic topology make this problem worse. An adaptive Multipath Multichannel Energy Efficient (AMMEE) routing strategy is proposed in this study, in which route selection strategies depend on forecasted energy consumption per packet, available bandwidth, queue length, and channel utilization. While multichannel uses a channel-ideal assignment process to lessen network collisions, multipath offers various paths and balances network strain. The link bandwidth is split up into a few sub-channels in the multichannel mechanism. To reduce network collisions, several source nodes simultaneously access the channel bandwidth. The cooperative multipath multichannel technique offers several paths from a single source or from several sources to the destination without colliding or becoming congested. The AMMEE routing approach is the basis for path selection. A load-and bandwidth-aware routing mechanism in the proposed AMMEE chooses the path based on node energy and forecasts their lifetime, which improves network dependability. The outcome demonstrates a comparative analysis of various multichannel medium access control (MMAC) techniques, including Parallel Rendezvous Multi Channel Medium Access Protocol (PRMMAC), Quality of Service Ad hoc On Demand Multipath Distance Vector (QoS-AOMDV), Q-learning-based Multipath Routing (QMR), and Topological Change Adaptive Ad hoc On-demand Multipath Distance Vector (TA-AOMDV) and the proposed AMMEE method. The results show that the AMMEE approach outperforms alternative systems.

In the big cities of Europe large-scale construction of apartment buildings took place at the end of the 19th and at the beginning of the 20th century. In the process, buildings were created based on unique plans, but very similar to each other, containing similar technological solutions and built from similar building materials. Over the past 100 years, some of the buildings have been continuously maintained, while the condition of other buildings has deteriorated significantly. The renovation of these buildings has now become necessary and in many cases, unavoidable. In the current economic and energy situation, it is important that maintenance or conversion is carried out in a sustainable manner to the necessary extent. The method and extent of the interventions can be provided in a uniform manner with help of a computer system. We have developed a condition assessment and decision support model and algorithm that can be used for this purpose. We call it Complex Building’s Decision Support System based on Fuzzy Signatures (CBDF system). We use fuzzy signature-based model to handle uncertainties, inaccuracies and possibly missing data that occur during the condition assessment. The presented decision model prepares the status assessment based on 4 main components (project info, knowledge base, preparatory work process, fuzzy system). After defining the objectives (e.g., general condition assessment, evaluation from the perspective of accident prevention, examination of the possibility of roof installation), the system requests the necessary data and generates the fuzzy signature required for the condition assessment of the given building. Based on the input data for the specific project and the knowledge base, the decision model searches for failures and anomalies in the building based on the preparatory work process, manages the existing uncertainties and inaccuracies, and determines the load bearing surplus of the examined load bearing structures. Using the existing information and conclusions, based on various fuzzy set-based descriptors and aggregation operators, the condition assessment is prepared, and then, if necessary, the intervention proposal as well. The final goal of the decision model is to put a tool in the hands of experts examining the condition of buildings, which can be used to prepare uniform and objective assessments (also suitable for ranking) and to reduce error in condition assessment.

In telerehabilitation., services are provided from a distance using telecommunication technologies. With the proliferation of broadband internet services and wireless networks., high-speed and low-latency data transmission can be maintained that allows for high quality audio and video communication. However., offline solutions without outsourcing of the computational need into the cloud are still required. Homecare solutions offer possibilities for rehabilitation of patients in their home environment. Guided workouts and training sessions can be automated and controlled with the help of cost-effective hardware and software applications. This paper presents first results of a latest development in homecare telerehabilitation with automated recognition of motion, evaluation and feedback.