The use of electronic health (eHealth) technologies in healthcare improves the quality of health services furnished to patients. The application of these technologies helps physicians and other health professionals to pursue early detection of abnormal status on patients' health. Body sensor networks are a type of wireless sensor networks aimed to be deployed on persons in order to collect physiological parameters for healthcare monitoring purposes. These BSNs are composed by several small sensors placed along patient's body, and capable to send (wirelessly) the collected health parameters to remote providers. BSNs need to operate every time and everywhere to transmit these important parameters to healthcare providers or automatic system to detect any anomaly in the patient health status. To provide this continuous monitoring of patients, it is mandatory to provide mobility support for the BSN so it can always be connected to some gateway to the Internet and therefore to back-end health providers. Several mechanisms with mobility support for mobile devices have been provided. However, the mobility support of a whole BSN has not been fully addressed. This article overviews available handover mechanisms used for wireless sensors mobility and proposes a new ubiquitous mobility approach for BSNs in healthcare. A case study with this new handover mechanism developed for a hospital infirmary is presented and highlights the gain of performances of the proposed solution.

The agro-industrial sector consumes a significant amount of natural resources for farming and meat production. By 2050, population growth is expected, generating more demand and, consequently, more consumption of scarce resources. This challenging scenario is a concern of the European Commission, revealed in the Green Deal commitment and by the United Nations’ 12th goal of sustainable development. Thus, organizations must increase productivity and be more sustainable as soon as possible. Internet of Things (IoT) is introduced as a solution to facilitate agro-food companies to be more eco-efficient, mainly facing difficulties on farms, such as food loss and waste, best efficiency in management of resources, and production. The deployment of this technology depends on the stage of maturity and potential of implementation. To assess and characterize companies, with respect of IoT implementation, a survey was applied in 21 micro, small and medium agro-food companies, belonging to milk, honey, olive oil, jams, fruticulture, bakery and pastry, meat, coffee, and wine sectors, in the central region of Portugal. As results, this paper reveals the stage of maturity, level of sophistication, potential, opportunities, solutions, and barriers for implementation of IoT. Additionally, suggestions and recommendations to improve practices are discussed.

Precision irrigation and optimization of water use have become essential factors in agriculture because water is critical for crop growth. The proper management of an irrigation system should enable the farmer to use water efficiently to increase productivity, reduce production costs, and maximize the return on investment. Efficient water application techniques are essential prerequisites for sustainable agricultural development based on the conservation of water resources and preservation of the environment. In a previous work, an off-policy deep reinforcement learning model, Deep Q-Network, was implemented to optimize irrigation. The performance of the model was tested for tomato crop at a site in Portugal. In this paper, an on-policy model, Advantage Actor–Critic, is implemented to compare irrigation scheduling with Deep Q-Network for the same tomato crop. The results show that the on-policy model Advantage Actor–Critic reduced water consumption by 20% compared to Deep Q-Network with a slight change in the net reward. These models can be developed to be applied to other cultures with high production in Portugal, such as fruit, cereals, and wine, which also have large water requirements.

Weeds, pathogens, and animal pests are among the pests that pose a threat to the productivity of crops meant for human consumption. Bird-caused crop losses pose a serious and costly challenge for farmers. This work presents a survey on bird deterrent solutions for crop protection. It first introduces the related concepts. Then, it provides an extensive review and categorization of existing methods, techniques, and related studies. Further, their strengths and limitations are discussed. Based on this review, current gaps are identified, and strategies for future research are proposed.

Over the years some medical studies have tried to better understand the internal behavior of human beings. Many researchers in this domain have been striving to find relationships between intra-vaginal temperature and certain female health conditions, such as ovulation and fertile period since woman’s intra-vaginal temperature is one of the body parameters most preferred in such studies. However, due to lack of a appropriate technology, medical research devoted to studying correlations of such body parameters with certain womans’ body phenomena could not obtain better results. This article presents the design and implementation of a novel intra-body sensor for acquisition and monitoring of intra-vaginal temperatures. This novel intra-body sensor provides data collection that is used for studying the relation between temperature variations and female health conditions, such as anticipation and monitoring of the ovulation period, detection of pregnancy contractions, preterm labor prevention, etc.. The motivation for this work focuses on the development of this new intra-body sensor that will represent a major step in medical technology. The novel sensor was tested and validated on hospitalized women as well as normal healthy women. Finally our medical team has attested to the accuracy, usability and performance of this novel intra-body sensor.