TL;DR: In this paper, network coding combined with opportunistic routing is used to improve energy efficiency in wireless IoT infrastructure, considering the existence of link correlation and a novel smart routing method to accurately estimate the number of transmissions required by forwarders.
Abstract: Modern Internet of Things (IoT) applications are heavily data driven and often require reliable data streams to achieve high-quality data mining. The concept of edge computing is introduced to reduce data latency and communication bandwidth between the cloud server and IoT edge devices. However, inefficient routing that may cause transmission failure or unnecessary data (re)transmission is still a key obstacle to obtain good and reliable data mining results. In this paper, network coding combined with opportunistic routing is used to improve energy efficiency in wireless IoT infrastructure, considering the existence of link correlation. Studies have shown that packet receptions on wireless links are correlated, which is completely contrary to the assumption of link independence used in existing routing mechanisms. This assumption causes estimation errors in the calculation of expected number of transmissions for forwarders, which further affects the selection of forwarder set, and ultimately affects the performance of the protocol. We propose an intra-session network coding mechanism based on the mining of link correlation. A novel smart routing method is proposed to accurately estimate the number of transmissions required by forwarders, together with an algorithm for selecting a forwarder set with more optimal number of transmissions. Simulation results demonstrate that the proposed mechanism can achieve fewer transmissions and offer more energy efficient communications for wireless edge IoT applications.
TL;DR: In this paper, the productivity of cut-to-length harvesting and forwarding in thinning and final felling using a routinely recorded follow-up dataset was analyzed using a range of stand-based productivity models for both harvesters and forwarders.
Abstract: Modern computerization facilitates data-gathering from forest machines, and offers new opportunities to develop models for predicting productivity in forest harvest operations. In this study, we analyze the productivity of cut-to-length harvesting and forwarding in thinning and final felling using a routinely recorded follow-up dataset. The data originate from over 700 machines that, over a 3-year period, harvested and forwarded more than 20 million m3 of round-wood from upwards of 20 thousand stands, making the dataset larger than any that has previously been used for productivity modelling. Results comprise a range of stand-based productivity models of varying complexity for both harvesters and forwarders. Mean stem size was the most influential variable for harvesting productivity: modelling based on mean stem size explained 57.6% of the variance in thinnings and 55.3% in final fellings. However, accurate predictions of forwarding productivity required the simultaneous consideration of several variable...
TL;DR: Evaluation of effects of forwarder tyre inflation pressure on rutting and soil compaction after final felling in Swedish forestry suggests that density increases occur earlier in the 600 kPa treatment than in the other treatments.
Abstract: In Swedish forestry, final felling is usually done by a harvester and a forwarder. These machines are heavy and the risk for rutting and soil compaction can be considerable under unfavourable soil conditions. The aim of this study was to evaluate effects of forwarder tyre inflation pressure on rutting and soil compaction after final felling. Three levels of forwarder tyre pressure were studied, 300, 450 and 600 kPa, after 2 and 5 machine passages. The first passage was driven with a 19.7 Mg harvester, and the second to fifth passages with a fully loaded forwarder totalling 37.8 Mg. Rut depths were not significant affected by tyre pressures but increased significantly with the number of machine passages. Soil density was significantly increased by 0.075 Mg m(-3) by the harvester passage. Soil density increased significantly with increasing number of forwarder passages, and tyre pressure did not significantly influence this increase but the interaction between number of forwarder passages and tyre pressure was almost significant. Data suggest that density increases occur earlier in the 600 kPa treatment than in the other treatments. Only parts of an area harvested are trafficked in a normal harvesting operation. Outside the research area approximately 12.5 per cent of the area harvested was covered with ruts. On primary strip roads, which are heavily trafficked, soil compaction cannot be avoided by reducing the tyre pressure. On secondary strip roads, not passed more than once by the forwarder, a low forwarder tyre pressure may reduce soil compaction. Language: en
TL;DR: It is shown that the intelligent forwarders can provide the remote sensors with context-awareness and transmit only important information to the big data server for analytics when certain behaviours happen and avoid overwhelming communication and data storage.
Abstract: An increasing number of the elderly population wish to live an independent lifestyle, rather than rely on intrusive care programmes. A big data solution is presented using wearable sensors capable of carrying out continuous monitoring of the elderly, alerting the relevant caregivers when necessary and forwarding pertinent information to a big data system for analysis. A challenge for such a solution is the development of context-awareness through the multidimensional, dynamic and nonlinear sensor readings that have a weak correlation with observable human behaviours and health conditions. To address this challenge, a wearable sensor system with an intelligent data forwarder is discussed in this paper. The forwarder adopts a Hidden Markov Model for human behaviour recognition. Locality sensitive hashing is proposed as an efficient mechanism to learn sensor patterns. A prototype solution is implemented to monitor health conditions of dispersed users. It is shown that the intelligent forwarders can provide the remote sensors with context-awareness. They transmit only important information to the big data server for analytics when certain behaviours happen and avoid overwhelming communication and data storage. The system functions unobtrusively, whilst giving the users peace of mind in the knowledge that their safety is being monitored and analysed.
TL;DR: In this paper, the authors studied the effect of three single-grip harvester work techniques on the productivity of logging residue recovery for energy and found that more than 50% of the forwarder's work time was spent on loading the residues.
Abstract: Vast quantities of logging residue are left behind on clearcut areas. Given the suitable transportation distance, environmental and economic circumstances, they provide a possible alternative for fossil fuels. However, distribution of residual biomass over large areas during the logging operation and trampling by machines hinders the recovery. The recovery enhancing effect of three single-grip harvester work techniques on the productivity of logging residue recovery for energy was studied. Forwarder productivity, distribution of effective work time, forwarding distance, load size and the residue yield were studied. A heavy forwarder with an enlarged 22 m 3 load space was used. The average load size was 9 tonnes. More than 50% of the forwarder's work time was spent on loading the residues. The recovery output of the trampled residues from the strip road after a conventional harvesting method was 11.4 t/E 0 -h for a 9 tonnes load and a 300 m transportation distance. In contrast, the single-grip harvester methods that aimed at the post-logging residue recovery increased the recovery output to 12.0–13.3 t/E 0 -h. The load size was a more significant factor than the forwarding distance in terms of machine productivity. The yield of residue recovery after the conventional roundwood harvesting method was 58.4% and from 66.8% to 78.7% for the alternative single-grip-harvester methods.