Towards More Sustainable Pavement Management Practices Using Embedded Sensor Technologies

Road agencies are constantly being placed in difficult situations when making road maintenance and rehabilitation decisions as a result of diminishing road budgets and mounting environmental concerns for any chosen strategies. This has led practitioners to seek out new alternative and innovative ways of monitoring road conditions and planning maintenance routines. This paper considers the use of innovative piezo-floating gate (PFG) sensors and conventional strain gauges to continuously monitor the pavement condition and subsequently trigger maintenance activities. These technologies can help develop optimized maintenance strategies as opposed to traditional ad-hoc approaches, which often lead to poor decisions for road networks. To determine the environmental friendliness of these approaches, a case study was developed wherein a life cycle assessment (LCA) exercise was carried out. Observations from accelerated pavement testing over a period of three months were used to develop optimized maintenance plans. A base case is used as a guide for comparison to the optimized systems to establish the environmental impacts of changing the maintenance workflows with these approaches. On the basis of the results, the proposed methods have shown that they can, in fact, produce environmental benefits when integrated within the pavement management maintenance system.

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Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions

Applied Sciences ◽

10.3390/app11062458 ◽

2021 ◽

Vol 11 (6) ◽

pp. 2458

Author(s):

Ronald Roberts ◽

Laura Inzerillo ◽

Gaetano Di Mino

Keyword(s):

Deep Learning ◽

Management Practices ◽

Prediction Models ◽

Road Networks ◽

Pavement Management ◽

Efficient Operation ◽

Pavement Maintenance ◽

Goods And Services ◽

Maintenance Decisions ◽

Computational Systems

Road networks are critical infrastructures within any region and it is imperative to maintain their conditions for safe and effective movement of goods and services. Road Management, therefore, plays a key role to ensure consistent efficient operation. However, significant resources are required to perform necessary maintenance activities to achieve and maintain high levels of service. Pavement maintenance can typically be very expensive and decisions are needed concerning planning and prioritizing interventions. Data are key towards enabling adequate maintenance planning but in many instances, there is limited available information especially in small or under-resourced urban road authorities. This study develops a roadmap to help these authorities by using flexible data analysis and deep learning computational systems to highlight important factors within road networks, which are used to construct models that can help predict future intervention timelines. A case study in Palermo, Italy was successfully developed to demonstrate how the techniques could be applied to perform appropriate feature selection and prediction models based on limited data sources. The workflow provides a pathway towards more effective pavement maintenance management practices using techniques that can be readily adapted based on different environments. This takes another step towards automating these practices within the pavement management system.

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Dietary condensed tannins in bovine faeces and effects on soil microbial dynamics: are there environmental benefits for cattle production systems?

Animal Production Science ◽

10.1071/an20118 ◽

2021 ◽

Vol 61 (7) ◽

pp. 690

Author(s):

Gisele M. Fagundes ◽

Gabriela Benetel ◽

Mateus M. Carriero ◽

Ricardo L. M. Sousa ◽

Kelly C. Santos ◽

...

Keyword(s):

Organic Matter ◽

Condensed Tannins ◽

Nutrient Dynamics ◽

Management Practices ◽

Production Systems ◽

Environmental Benefits ◽

Nutrient Inputs ◽

Microbial Dynamics ◽

Soil Microbial ◽

Soil Microbial Population

Context Plant bioactive compounds such as condensed tannins (CT) are seen as an alternative to rumen chemical modulators to mitigate rumen methanogenesis in livestock; however, the presence of CT in ruminant faeces also produces a series of changes in soil microbiomes. Little is known about these effects on soil nutrient dynamics. Therefore, whether CT affect the decomposition process of faecal organic matter, delaying it and consequently increasing soil carbon and nitrogen (N) sequestration, merits study. Aims Our study investigated the effects of a diet rich in CT on bovine faecal composition and on subsequent dynamics of a soil microbial population. Methods Faeces were analysed from cattle fed the following diets: control (no CT), 1.25% CT, 2.5% CT. In a greenhouse pot experiment over a period of 60 days, faeces from the three dietary treatments were applied to soil and the soil microbial populations were measured against a control with no faeces applied. Key results The presence of CT increased the excretion of faecal N and of neutral and acid detergent fibres and lignin, and the higher rate of CT reduced the rate of soil organic matter decomposition. Treatments with dietary CT resulted in greater total numbers of bacteria in the soil than in the no-faeces control and stimulated numbers of Actinobacteria, Proteobacteria (α-Proteobacteria) and Firmicutes. Conclusions The study showed that CT alter N recycling and other nutrient inputs in a soil–animal ecosystem by increasing faecal N inputs, delaying organic matter breakdown, and changing soil microbial dynamics. Implications The presence of CT in ruminant diets can be beneficial to the soil environment. Sustainable management practices should be encouraged by providing ruminants with feed including high-CT legumes in silvopastoral systems.

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