Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

SOC Module for IOT Based Smart Water Monitoring

The Internet of Things (IoT) has provided promising opportunities to create powerful industrial and domestic applications. One of its main applications is smart metering. The existing analogue meter in residential area requires consistent human monitoring, which leads to computational errors. Huge labor force, their negligence and money invested are the drawback of such meters. Therefore, a cost effective and low power smart-meter that can monitor the daily consumption of water in residential area need to be developed, in order to conserve water. Here in this research, SOC based smart water meter is developed to provide cost effective solution. Further, the developed system is implemented in real time to investigate the reliability and feasibility

Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities

Optimization of energy consumption in future intelligent energy networks (or Smart Grids) will be based on grid-integrated near-real-time communications between various grid elements in generation, transmission, distribution and loads. This paper discusses some of the challenges and opportunities of communications research in the areas of smart grid and smart metering. In particular, we focus on some of the key communications challenges for realizing interoperable and future-proof smart grid/metering networks, smart grid security and privacy, and how some of the existing networking technologies can be applied to energy management. Finally, we also discuss the coordinated standardization efforts in Europe to harmonize communications standards and protocols.Comment: To be published in IEEE Communications Surveys and Tutorial

EnerMon: IoT power monitoring system for smart environments

In this research work, we describe the development and subsequent validation of EnerMon a flexible, efficient, edge-computing based IoT LoRa System to monitor power consumption. This system provides real-time information and a descriptive analytics process to provide a ‘big picture’ about energy consumption over time and identify energetic waste. The solution is based on Arduinos, Current Transformer Sensors, Raspberry PI as an application server and LoRa communication alongside a description and information on what is to be expected of it. It describes the development process from the Design phase to the Validation phase with all the steps in between. Due to LoRa low debit communication, an edge computing approach was implemented to create a real-time monitoring process based on this technology. This solution, with the help of descriptive analysis, allows the creation of an energetic local footprint, using a low-cost developed solution for less than 80€ per three-phases monitoring device. It also allows for an easy installation without communication range and obstacles limitations making it easy to be used in a different set of situations from big complex building to smaller consumers, such as electric boilers, or simply to measure the energetic footprint of tourists in a small local tourist apartment.O presente estudo, realizado no âmbito da tese de mestrado, descreve o desenvolvimento e subsequente validação de EnerMon, um sistema IoT(Internet of Things / Internet das Coisas) LoRa flexível, eficiente e baseado em edge-computing capaz de monitorizar consumo de energia em tempo real. Através de processos de análise descritiva é também apresentada uma visão geral sobre o consumo energético ao longo do tempo com a identificação de desperdícios de energia. Neste trabalho o leitor irá tomar conhecimento do processo de desenvolvimento completo do sistema, desde a fase de design à fase de testes, criado com o uso de Arduinos, Sensores de transformadores de corrente e Raspberry PIs como servidores aplicacionais, bem como informação relacionada com a comunicação LoRa e o que lhe é expectável. Esta solução, com a ajuda de analíticas descritivas, permitem a identificação de pegadas energéticas locais, usando materiais de baixo custo por menos de 80€ por sensor de monitorização de três fases. Permite também a fácil instalação sem limitações de alcance e obstáculos na comunicação, simplificando a sua utilização em diferentes ambientes desde edifícios complexos a consumidores energéticos mais pequenos, como caldeiras elétricas ou simplesmente medir a pegada energética de turistas em alojamento local

FireFly Mosaic: A Vision-Enabled Wireless Sensor Networking System

Abstract — With the advent of CMOS cameras, it is now possible to make compact, cheap and low-power image sensors capable of on-board image processing. These embedded vision sensors provide a rich new sensing modality enabling new classes of wireless sensor networking applications. In order to build these applications, system designers need to overcome challanges associated with limited bandwith, limited power, group coordination and fusing of multiple camera views with various other sensory inputs. Real-time properties must be upheld if multiple vision sensors are to process data, com-municate with each other and make a group decision before the measured environmental feature changes. In this paper, we present FireFly Mosaic, a wireless sensor network image processing framework with operating system, networking and image processing primitives that assist in the development of distributed vision-sensing tasks. Each FireFly Mosaic wireless camera consists of a FireFly [1] node coupled with a CMUcam3 [2] embedded vision processor. The FireFly nodes run the Nano-RK [3] real-time operating system and communicate using the RT-Link [4] collision-free TDMA link protocol. Using FireFly Mosaic, we demonstrate an assisted living application capable of fusing multiple cameras with overlapping views to discover and monitor daily activities in a home. Using this application, we show how an integrated platform with support for time synchronization, a collision-free TDMA link layer, an underlying RTOS and an interface to an embedded vision sensor provides a stable framework for distributed real-time vision processing. To the best of our knowledge, this is the first wireless sensor networking system to integrate multiple coordinating cameras performing local processing. I

Energy and Water Monitoring for a Large Social Housing Intervention in Northern Italy

In recent years, the awareness of the problem of the performance gap and rebound effect extends the interest in assessing the real operation of buildings, in assessing how buildings match users' needs once they are occupied, and in understanding how occupants' behavior affects the actual building performance. The paper discusses the case study and presents the results of a monitoring campaign of 2 years of occupancy of a large social housing intervention recently built near Milan, for a total of 152 flats. Data about the thermal energy consumption for heating and cooling, the domestic hot and cold water use, and the occupants' intervention on controlling devices are assessed and presented. The case study is representative of the actual design and construction of high-performing multi-family buildings in Italy. All the buildings are class A rated, very highly insulated, and ventilated with centralized mechanical ventilation systems with thermodynamic heat recovery. Centralized water-to-water heat pumps supply hot and refrigerated water for heating and cooling and domestic hot water as well. A building monitoring system is installed, able to track energy and water consumption, factors influencing the energy consumption not related to the building characteristics (weather data, operational setting) as well as the overall building performance data. The results show unexpected high energy and water consumption and moreover a large variability of the energy and water consumption pattern among the dwellings and between the years due to the significant influence of the occupants' behavior and habits

Wireless Sensor Networking in Challenging Environments

Recent years have witnessed growing interest in deploying wireless sensing applications in real-world environments. For example, home automation systems provide fine-grained metering and control of home appliances in residential settings. Similarly, assisted living applications employ wireless sensors to provide continuous health and wellness monitoring in homes. However, real deployments of Wireless Sensor Networks (WSNs) pose significant challenges due to their low-power radios and uncontrolled ambient environments. Our empirical study in over 15 real-world apartments shows that low-power WSNs based on the IEEE 802.15.4 standard are highly susceptible to external interference beyond user control, such as Wi-Fi access points, Bluetooth peripherals, cordless phones, and numerous other devices prevalent in residential environments that share the unlicensed 2.4 GHz ISM band with IEEE 802.15.4 radios. To address these real-world challenges, we developed two practical wireless network protocols including the Adaptive and Robust Channel Hopping (ARCH) protocol and the Adaptive Energy Detection Protocol (AEDP). ARCH enhances network reliability through opportunistically changing radio\u27s frequency to avoid interference and environmental noise and AEDP reduces false wakeups in noisy wireless environments by dynamically adjusting the wakeup threshold of low-power radios. Another major trend in WSNs is the convergence with smart phones. To deal with the dynamic wireless conditions and varying application requirements of mobile users, we developed the Self-Adapting MAC Layer (SAML) to support adaptive communication between smart phones and wireless sensors. SAML dynamically selects and switches Medium Access Control protocols to accommodate changes in ambient conditions and application requirements. Compared with the residential and personal wireless systems, industrial applications pose unique challenges due to their critical demands on reliability and real-time performance. We developed an experimental testbed by realizing key network mechanisms of industrial Wireless Sensor and Actuator Networks (WSANs) and conducted an empirical study that revealed the limitations and potential enhancements of those mechanisms. Our study shows that graph routing is more resilient to interference and its backup routes may be heavily used in noisy environments, which demonstrate the necessity of path diversity for reliable WSANs. Our study also suggests that combining channel diversity with retransmission may effectively reduce the burstiness of transmission failures and judicious allocation of multiple transmissions in a shared slot can effectively improve network capacity without significantly impacting reliability