To tackle the high prevalence of lameness, techniques to monitor cow locomotion are being developed in order to detect changes in cows’ locomotion due to lameness. Obviously, in such lameness detection systems, alerts should only respond to locomotion changes that are related to lameness. However, other environmental or cow factors can contribute to locomotion changes not related to lameness and hence, might cause false alerts. In this study the effects of wet surfaces, dark environment, age, production level, lactation and gestation stage on cow locomotion were investigated. Data was collected at Institute for Agricultural and Fisheries Research research farm (Melle, Belgium) during a 5-month period. The gait variables of 30 non-lame and healthy Holstein cows were automatically measured every day. In dark environments and on wet walking surfaces cows took shorter, more asymmetrical strides with less step overlap. In general, older cows had a more asymmetrical gait and they walked slower with more abduction. Lactation stage or gestation stage also showed significant association with asymmetrical and shorter gait and less step overlap probably due to the heavy calf in the uterus. Next, two lameness detection algorithms were developed to investigate the added value of environmental and cow data into detection models. One algorithm solely used locomotion variables and a second algorithm used the same locomotion variables and additional environmental and cow data. In the latter algorithm only age and lactation stage together with the locomotion variables were withheld during model building. When comparing the sensitivity for the detection of non-lame cows, sensitivity increased by 10% when the cow data was added in the algorithm (sensitivity was 70% and 80% for the first and second algorithm, respectively). Hence, the number of false alerts for lame cows that were actually non-lame, decreased. This pilot study shows that using knowledge on influencing factors on cow locomotion will help in reducing the number of false alerts for lameness detection systems under development. However, further research is necessary in order to better understand these and many other possible influencing factors (e.g. trimming, conformation) of non-lame and hence ‘normal’ locomotion in cows.

GMDSS alerting was introduced in order to automate the call for search and rescue of a ship in distress, through the utilization of the most modern terrestrial and celestial communication systems. However, the GMDSS suffers from the inefficiencies associated with equipment design, operator competence and, most importantly, with those relevant to the equipment–operator interface. The GMDSS inefficiencies are frequently manifested in the form of false alerts, which apart from using resources, degrade the overall effectiveness of the SAR operation. In this paper, the GMDSS post-full-implementation record of false alerts received by the Greek MRCC is presented and analyzed. The observed persistence of high incidence of false alerts dictates the need for the proposal of further measures to combat false alerts, to promote the intended mission of the system and to generally improve the safety of navigation at sea.