Although intelligent agent-based systems have existed for several years, the progression in terms of real applications or their integration in the industry have not yet reached the expected levels. During the last two decades, many agent platforms have appeared with the aim of simplifying the development of multi-agent systems. Some of these platforms have been designed for general purposes, while others have been oriented towards specific domains. However, the lack of standards and the complexity associated with supporting such systems, among other difficulties, have hampered their generalised use. This article looks in depth at the current situation of existing agent platforms, trying to analyse their current shortcomings and their expected needs in the near future. The goal of the paper is to identify possible lines of work and some of the most crucial aspects to be considered in order to popularize the application of agent technology as a dynamic and flexible solution to current problems. Moreover, the paper presents SPADE 3, a new version of the SPADE middleware, which has been totally redesigned in order to conform to the identified challenges. Finally, a case study is proposed to illustrate how SPADE 3 is able to fulfill these challenges.

This paper presents a multi-agent architecture that facilitates the development of real-time multi-agent systems based on the SIMBA approach. The approach allows the integration of unbounded deliberative processes with critical real-time tasks. CBP-BDI deliberative agents collaborate with ARTIS agents in order to solve real-time problems efficiently. The proposal has been successfully tested and evaluated in a case study based on the use of mobile robots for mail delivery.

Telemedicine and all types of monitoring systems have proven to be a useful and low-cost tool with a high level of applicability in cardiology. The objective of this work is to present an IoT-based monitoring system for cardiovascular patients. The system sends the ECG signal to a Fog layer service by using the LoRa communication protocol. Also, it includes an AI algorithm based on deep learning for the detection of Atrial Fibrillation and other heart rhythms. The automatic detection of arrhythmias can be complementary to the diagnosis made by the physician, achieving a better clinical vision that improves therapeutic decision making. The performance of the proposed system is evaluated on a dataset of 8.528 short single-lead ECG records using two merge MobileNet networks that classify data with an accuracy of 90% for atrial fibrillation.

Sustainable transportation is one of the major concerns in cities. This concern involves all type of movements motivated by different goals (mobility of citizens, transportation of goods and parcels, etc.). The main goal of this work is to provide an intelligent approach for Sustainable Last Mile Delivery, by reducing (or even deleting) the need of dedicated logistic moves (by cars, and/or trucks). The method attempts to reduce the number of movements originated by the parcels delivery by taking advantage of the citizens’ movements. In this way our proposal follows a crowdsourcing approach, in which the citizens that moves in the city, because of their own needs, become temporal deliverers. The technology behind our approach relays on Multi-agent System techniques and complex network-based algorithms for optimizing sustainable delivery routes. These artificial intelligent approaches help to reduce the complexity of the scenario providing an efficient way to integrate the citizens’ routes that can be executed using the different transportation means and networks available in the city (public system, private transportation, eco-vehicles sharing systems, etc.). A complex network-based algorithm is used for computing and proposing an optimized Sustainable Last Mile Delivery route to the crowd. Moreover, the executed tests show the feasibility of the proposed solution, together with a high reduction of the CO${}_2$ emission coming from the delivery trucks that, in the case studies, are no longer needed for delivery.