A multi-robot deep Q-learning framework for priority-based sanitization of railway stations.

Sanitizing railway stations is a relevant issue, primarily due to the recent evolution of the Covid-19 pandemic. In this work, we propose a multi-robot approach to sanitize railway stations based on a distributed Deep Q-Learning technique. The proposed framework relies on anonymous data from existing WiFi networks to dynamically estimate crowded areas within the station and to develop a heatmap of prioritized areas to be sanitized.

Effects of cow reproductive status, parity and lactation stage on behaviour and heavy breathing indications of a commercial accelerometer during hot weather conditions.

Heat stress presents one of the most urgent challenges to modern dairy farming, having major detrimental impacts on cow welfare, health, and production. Understanding the effect of cow factors (reproductive status, parity, and lactation stage) on the physiological and behavioural response to hot weather conditions is essential for the accurate detection and practical application of heat mitigation strategies. To study this, collars with commercial accelerometer-based sensors were fitted on 48 lactation dairy cows to record behaviour and heavy breathing from late spring to late summer.

Development of a New Wearable 3D Sensor Node and Innovative Open Classification System for Dairy Cows' Behavior.

Monitoring dairy cattle behavior can improve the detection of health and welfare issues for early interventions. Often commercial sensors do not provide researchers with sufficient raw and open data; therefore, the aim of this study was to develop an open and customizable system to classify cattle behaviors. A 3D accelerometer device and host-board (i.

Dairy Cow Behavior Is Affected by Period, Time of Day and Housing.

Dairy cow behavior is affected by external and endogenous factors, including time of year, barn microclimate, time of day and housing. However, little is known about the combined effects of these factors. Data were collected on eight farms in Northern Italy during summer, winter and a temperate season.

A Robotic Cognitive Control Framework for Collaborative Task Execution and Learning.

In social and service robotics, complex collaborative tasks are expected to be executed while interacting with humans in a natural and fluent manner. In this scenario, the robotic system is typically provided with structured tasks to be accomplished, but must also continuously adapt to human activities, commands, and interventions. We propose to tackle these issues by exploiting the concept of cognitive control, introduced in cognitive psychology and neuroscience to describe the executive mechanisms needed to support adaptive responses and complex goal-directed behaviors.

Describing the trend of ammonia, particulate matter and nitrogen oxides: The role of livestock activities in northern Italy during Covid-19 quarantine.

Nitrogen oxides (NOx), sulphur oxides (SOx) and ammonia (NH) are among the main contributors to the formation of secondary particulate matter (PM), which represent a severe risk to human health. Even if important improvements have been achieved worldwide, traffic, industrial activities, and the energy sector are mostly responsible for NOx and SOx release; instead, the agricultural sector is mainly responsible for NH emissions. Due to the emergency of coronavirus disease, in Italy schools and universities have been locked down from late February 2020, followed in March by almost all production and industrial activities as well as road transport, except for the agricultural ones.

Sound Analysis to Predict the Growth of Turkeys.

Protocols for manual weighing of turkeys are not practical on turkey farms because of the large body sizes, heavy weights and flighty nature of turkeys. The sounds turkeys make may be a proxy for bird weights, but the relationship between turkey sounds and bird weights has not been studied. The aim of this study was to correlate peak frequency (PF) of vocalization with the age and weight of the bird and examine the possibility using PF to predict the weight of turkeys.

A Survey of Dairy Cattle Behavior in Different Barns in Northern Italy.

Due to its increasing pressure on dairy cows, studies that investigate how to cope with heat stress are needed. The heat stress affects multiple aspects of cows' lives, among which their behavior and welfare. In this study, a survey was carried out in eight farms located in Northern Italy to monitor and evaluate the environmental aspects of the barns and the behavioral responses of dairy cows.

Effects of Climatic Conditions on the Lying Behavior of a Group of Primiparous Dairy Cows.

Currently, lying behavior can be assessed using continuous observations from sensors (e.g., accelerometers).

Effect of ammonia stripping and use of additives on separation of solids, phosphorus, copper and zinc from liquid fractions of animal slurries.

To increase the sustainable reuse of animal manure as fertiliser, in many cases suitable treatment techniques are needed to modify the composition and obtain a balanced nutrient content. This study was conducted to evaluate the best strategies to remove solids, P, Cu and Zn, using two additives Ca(OH) and Al(SO), in combination with an ammonia stripping process. The assessment was carried out on five type of liquid fractions derived from the mechanical separation of: raw pig slurry, pig digested slurry, pig digested slurry after ammonia stripping, pig and cattle digested slurry, pig and cattle digested slurry after ammonia stripping.

Effects of Feeding Frequency on the Lying Behavior of Dairy Cows in a Loose Housing with Automatic Feeding and Milking System.

Management systems in modern dairy farms is an important issue in relation to animal comfort and welfare. The objective of this study was to determine the effect of feed delivery frequency on the behavior patterns, visits to an automatic milking system (AMS) and on milk production of lactating dairy cows. The study was conducted on a commercial dairy farm with automatic feeding and milking systems.

Review: Environmental impact of livestock farming and Precision Livestock Farming as a mitigation strategy.

This paper reviews the environmental impact of current livestock practices and discusses the advantages offered by Precision Livestock Farming (PLF), as a potential strategy to mitigate environmental risks. PLF is defined as: "the application of process engineering principles and techniques to livestock farming to automatically monitor, model and manage animal production". The primary goal of PLF is to make livestock farming more economically, socially and environmentally sustainable and this can be obtained through the observation, interpretation of behaviours and, if possible, individual control of animals.

Nitrogen removal from digested slurries using a simplified ammonia stripping technique.

This study assessed a novel technique for removing nitrogen from digested organic waste based on a slow release of ammonia that was promoted by continuous mixing of the digestate and delivering a continuous air stream across the surface of the liquid. Three 10-day experiments were conducted using two 50-L reactors. In the first two, nitrogen removal efficiencies were evaluated from identical digestates maintained at different temperatures (30°C and 40°C).

Effect of a Biological Additive on Nitrogen Losses from Pig Slurry during Storage.

Additives applied to animal manure slurries can affect the chemical composition and the biological processes of slurries during storage, with possible improvement of their management and reduction of environmental problems. Some new formulations are marketed claiming a nitrogen (N) removal effect due to denitrification, with the consequence of a reduced N content in the manure after storage. This study evaluated the effects of one of these commercial additives (BACTYcomplex) on slurry characteristics and N losses at a commercial piggery.

The role of intrinsic motivations in attention allocation and shifting.

The concepts of attention and intrinsic motivations are of great interest within adaptive robotic systems, and can be exploited in order to guide, activate, and coordinate multiple concurrent behaviors. Attention allocation strategies represent key capabilities of human beings, which are strictly connected with action selection and execution mechanisms, while intrinsic motivations directly affect the allocation of attentional resources. In this paper we propose a model of Reinforcement Learning (RL), where both these capabilities are involved.