When it comes to securing IoT communication, it is critical to employ secure communication technologies that can ensure that sensitive information exchanged between IoT devices and fog/edge/cloud services remains confidential. Since typical IoT devices are resource-constraint, it is challenging to use and deploy secure IoT protocols on such devices: It is thus critical to study the overhead of such protocols for resource-constrained devices, as it significantly affects the performance of an overall IoT solution. In this paper, we analyze the secure variants of the widely used messaging protocol MQ Telemetry Transport (MQTT), namely MQTT with TLS and MQTT with AES. We report the results of our performance evaluation in the context of an IoT solution for Precision Agriculture using an STM32 microcontroller with an NB-IoT module to compare these variants with plain MQTT and determine the most appropriate options based on the amount of data transmitted and achieved security level.
The paper evaluates the usability of remote satellite-based and proximal ground-based agrometeorological data sources for precision agriculture and crop production in Croatia. The compared agrometeorological datasets stem from the open-access data sources Copernicus CDS and the Agri4Cast portal, and commercial in situ agrometeorological stations (PinovaMeteo) which monitor environmental parameters relevant to the physiological state of crops. The study compares relevant parameters for 10 different locations in Croatia for three consecutive years (2019, 2020, and 2021) to investigate whether model-based data from ERA5-Land and Agri4Cast are well-correlated with ground measurements from independent in situ stations (PinovaMeteo) for specific agrometeorological parameters (air and soil temperature, and precipitation). Our results indicate the following: both the ERA5-Land and Agri4Cast datasets show mostly strong positive correlations with ground observations for air temperature, modest correlations for soil temperature, but modest or even low correlations for precipitation. Analysis of the residuals indicates higher overall residual values, especially in areas with complex topography and near large bodies of water or the sea, and deviations of residuals that may limit the usability of satellite- and model-based data for decision-making in agriculture.
Detection of human activities is a set of techniques that can be used in wide range of applications, including smart homes and healthcare. In this paper we focus on activity detection in a smart home environment, more specifically on detecting entrances to a room and exits from a room in a home or office space. This information can be used in applications that control HVAC (heating, ventilation, and air conditioning) and lighting systems, or in Ambient Assisted Living (AAL) applications which monitor the people's wellbeing. In our approach we use data from two simple sensors, passive infrared sensor (PIR) which monitors presence and hall effect sensor which monitors whether the door is opened or closed. This installation is non-intrusive and quite simple because the sensor node to which sensors are connected is battery powered, and no additional work to ensure power supply needs to be performed. Two approaches for activity detection are proposed, first based on a sliding window, and the other based on artificial neural network (ANN). The algorithms are tested on a dataset collected in our laboratory environment.
Next Generation Networks (NGN) aim to offer a wide variety of advanced telecommunications and multimedia services. Introduction of these services will be enabled mainly by two factors: increased bandwidth in the access network and convergence of different legacy networks towards a universal all-IP core network. The offer of large number of services in the NGN environment will arise the need for service provisioning and management procedures. Service management on emerging telecommunication systems that are distributed over a wide area is a hard task because it is not easy or even possible to perform final testing on a remote target system, as well as on system in operation [1-3]. Experiences show that it is possible for new software running on a target system to give a result different from the one obtained on test system [4]. The reasons are mostly the structural and/or functional differences between both systems. Therefore, only implementation and testing on the actual target system can give the answer whether the new software solves the problem (i.e., error, new operational circumstances, enhancement, and maintainability improvement) or not. Service management and software configuration operations in distributed systems become very demanding tasks as the number of computers and/or geographical distances between them grow. The situation gets worse with an increase in the complexity of the network and the number of nodes. This paper describes a method for service provisioning in an environment with a large number of distributed network servers and different versions of services placed across them. We have developed the agent based system called Remote Maintenance Shell (RMS) capable for remote control and management of services. To be specific, we present solutions for getting the service to the right place, starting it, and providing maintenance (upgrading with new versions). We have defined possible service distribution strategies for execution of operations and in this paper we consider applying of self-organized agents as a possible solution for this problem. PROCEEDINGS OF THE WORKSHOP ON APPLICATIONS OF SOFTWARE AGENTS ISBN 978-86-7031-188-6, pp. 18 24, 2011
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