An Efficient Interface for the Integration of IoT Devices with Smart Grids

Abstract

The evolution of computing devices and ubiquitous computing has led to the development of the Internet of Things (IoT). Smart Grids (SGs) stand out among the many applications of IoT and comprise several embedded intelligent technologies to improve the reliability and the safety of power grids. SGs use communication protocols for information exchange, such as the Open Smart Grid Protocol (OSGP). However, OSGP does not support the integration with devices compliant with the Constrained Application Protocol (CoAP), a communication protocol used in conventional IoT systems. In this sense, this article presents an efficient software interface that provides integration between OSGP and CoAP. The results obtained demonstrate the effectiveness of the proposed solution, which presents low communication overhead and enables the integration between IoT and SG systems.

A Comprehensive Review on Smart Grids: Challenges and Opportunities

“…Table 3 shows that most of the Encryption issues do not clearly define the algorithms they use, although there are some articles that use Multi-dimensional Data aggregation and even Cognitive Risk Control. Multi-dimensional Data aggregation [42,[55][56][57]60,62,64] Cognitive Risk Control [37,82] Not Defined [19,20,[22][23][24]26,28,29,31,35,36,38,39,43,[45][46][47][48]50,[52][53][54]58,61,63,73,[76][77][78][79]81,[98][99][100][101][102][103][104][105]…”

“…The works of Alonso et al [70] and Cavalieri [89] using the IEC61850 Protocol can be highlighted, showing us an applicable field of research with a view to homogenizing the algorithms and protocols used by Smart Grids and achieve an integration of all elements that conform them. Green-RPL [53] Local positive degree coupling [44] IEE 802.11s [33] Web Of Energy [67] Dynamic Barrier Coverage [68] IEC61850 [70,89] Wind-driven bacterian foraging algorithm [86] Data Slicing [87] TSUBE energy trading algorithm [91] Stochastic Geometry [92] Rectangular quadrature amplitude modulation [37] Policy-based group authentication algorithm [103] Mapping interface integration COIIoT [99,104] Nash Equilibrium (NE) and the Bayesian NE [105] Wireless sensor network protocol [35,50,53,63,73,[76][77][78]98,108,110] Algorithmic Approach [36,37,48,52,93,107,109] Furthermore, Figure 6c shows the Protocols Applied in Smart Grid Algorithms, pointing out that these technologies are varied and abundant, since 46% concentrate 14 different protocols applied among members or nodes of the Smart Grid. In addition, 34% is located in wireless connections of Sensor Networks and 20% Algorithmic Approaches inside these networks.…”

“…SGs exchange information by applying communication protocols like the Open Smart Grid Protocol (OSGP) but failing to integrate with devices compliant with the Constrained Application Protocol (CoAP). Viel et al [104] proposed a mapping interface integration between OSGP and CoAP, called COIIoT, to enable the communication among IoT devices used in home and industry applications and SG infrastructure. COIIoT also translates the methods utilized in every protocol by means of a set of mapping functions at low-cost and low-impact in communication.…”

Multispectral Cameras and Machine Learning Integrated into Portable Devices as Clay Prediction Technology

“…Since single-board computers have become more accessible to the general public, the Raspberry Pi has become one of the more popular systems, mainly in the scientific community, promoting research in IoT and all features involved [16,17]. Leithardt et al [18] and Felipe Viel et al [19] developed works that exemplified the application of the Raspberry Pi in IoT.…”

Synthetic Energy Data Generation Using Time Variant Generative Adversarial Network

“…Hence, in this work, we focused on implementing underlying GAN method to study data consumed by electrical energy appliances over the period of time and generate synthetic data similar to that of real dataset. The idea of using energy consumption data is greatly influenced from smart grid research done by authors based on energy data in [2,10]. The aim of this work is to model generative adversarial network on energy consumption data and generate synthetic data indistinguishable from the real dataset in terms of data characteristics.…”