With the increase in global life expectancy and the advance of technology, the creation of age-friendly environments is a priority in the design of new products for elderly people healthcare. This paper presents a proposal for a real-time health monitoring system of older adults living in geriatric residences. This system was developed to help caregivers to have a better control in monitoring the health of their patients and have closer communication with their patients’ family members. To validate the feasibility and effectiveness of this proposal, a prototype was built, using a biometric bracelet connected to a mobile application, which allows real-time visualization of all the information generated by the sensors (heart rate, body temperature, and blood oxygenation) in the bracelet. Using these data, caregivers can make decisions about the health status of their patients. The evaluation found that the users perceived the system to be easy to learn and use, providing initial evidence that our proposal could improve the quality of the adult’s healthcare.

This paper presents the usability assessment of the design of an Internet of Medical Things (IoMT) system for older adults; the evaluation, using heuristics, was held early on the design process to assess potential problems with the system and was found to be an efficient method to find issues with the application design and led to significant usability improvements on the IoMT platform.

Real-life implementation of the Internet of Things (IoT) in healthcare requires sufficient quality of service (QoS) to transmit the collected data successfully. However, unsolved challenges in prioritization and congestion issues limit the functionality of IoT networks by increasing the likelihood of packet loss, latency, and high-power consumption in healthcare systems. This study proposes a priority-based cross-layer congestion control protocol called QCCP, which is managed by communication devices’ transport and medium access control (MAC) layers. Unlike existing methods, the novelty of QCCP is how it estimates and resolves wireless channel congestion because it does not generate control packets, operates in a distributed manner, and only has a one-bit overhead. Furthermore, at the same time, QCCP offers packet scheduling considering each packet’s network load and QoS. The results of the experiments demonstrated that with a 95% confidence level, QCCP achieves sufficient performance to support the QoS requirements for the transmission of health signals. Finally, the comparison study shows that QCCP outperforms other TCP protocols, with 64.31% higher throughput, 18.66% less packet loss, and 47.87% less latency.

Intelligence capabilities will be the cornerstone in the development of next-generation cognitive networks. These capabilities allow them to observe network conditions, learn from them, and then, using prior knowledge gained, respond to its operating environment to optimize network performance. This study aims to offer an overview of the current state of the art related to the use of deep learning in applications for intelligent cognitive networks that can serve as a reference for future initiatives in this field. For this, a systematic literature review was carried out in three databases, and eligible articles were selected that focused on using deep learning to solve challenges presented by current cognitive networks. As a result, 14 articles were analyzed. The results showed that applying algorithms based on deep learning to optimize cognitive data networks has been approached from different perspectives in recent years and in an experimental way to test its technological feasibility. In addition, its implications for solving fundamental challenges in current wireless networks are discussed.

In this paper we propose the application of intelligent agents in traffic-lights, for the road control of urban transit in the city of Colima, México; using a multi-agent approach for dynamic urban traffic-lights system coordination that relies on locally available traffic data and the traffic condition of the neighboring intersections. According to this approach, our system consists of agents distributed into a hierarchical architecture. Each agent is responsible for one activity, for example, traffic data collection, preprocessing of these data and decision making of reconfiguration of the traffic-lights controllers. An intelligent algorithm based on the policy management model is defined and used as an auxiliary element for the coordination mechanism in order to form an adaptive control system with learning capabilities that allows a more fluid traffic and reduce some of the problems that the society face such as the average wait time and trip travel time and the average size queue per intersection. We define a model based on configuration profiles that are used as initial configurations and new configuration profiles are created as the traffic conditions change. Our approach is experimented with traffic control of a few connected junctions and the result obtained is promising; it can reduce the average delayed time of each car at each traffic-light near an intersection rather substantially when compared with the current traffic-lights control approach.

The rapid development if society has generated an increasing number of human activities that have gradually modified the marine environement. Wirless sensor networks have been considered as potentially promising alternative for monitoring marine environment. Usually the topology of the monitoring system is formed by a group of fixed buoys that gather data, and a coordinator node is responsible to sent the data to a processing center. This topology does not demand a routing protocol. However some situations as the monitoring of the behavior of currents demands mobility of the buoys and as a consequence a more complex communication mechanism in order to send the information to the processing center. This paper presents HYRMA, a cluster-based hybrid routing protocol focused on the reduction of energy consumption which is applied in a marine environmental. Based on the results obtained from simulator, HYRMA is shown to be a suitable mechanism for data transmissions in a WSN applied in a marine environment.