Toward an Intelligent Campus: IoT Platform for Remote Monitoring and Control of Smart Buildings.

With the growing need to obtain information about power consumption in buildings, it is necessary to investigate how to collect, store, and visualize such information using low-cost solutions. Currently, the available building management solutions are expensive and challenging to support small and medium-sized buildings. Unfortunately, not all buildings are intelligent, making it difficult to obtain such data from energy measurement devices and appliances or access such information. The internet of things (IoT) opens new opportunities to support real-time monitoring and control to achieve future smart buildings. This work proposes an IoT platform for remote monitoring and control of smart buildings, which consists of four-layer architecture: power layer, data acquisition layer, communication network layer, and application layer. The proposed platform allows data collection for energy consumption, data storage, and visualization. Various sensor nodes and measurement devices are considered to collect information on energy use from different building spaces. The proposed solution has been designed, implemented, and tested on a university campus considering three scenarios: an office, a classroom, and a laboratory. This work provides a guideline for future implementation of intelligent buildings using low-cost open-source solutions to enable building automation, minimize power consumption costs, and guarantee end-user comfort.

Design and Implementation of a Cloud-IoT-Based Home Energy Management System.

The advances in the Internet of Things (IoT) and cloud computing opened new opportunities for developing various smart grid applications and services. The rapidly increasing adoption of IoT devices has enabled the development of applications and solutions to manage energy consumption efficiently. This work presents the design and implementation of a home energy management system (HEMS), which allows collecting and storing energy consumption data from appliances and the main load of the home. Two scenarios are designed and implemented: a local HEMS isolated from the Internet and relies on its processing and storage duties using an edge device and a Cloud HEMS using AWS IoT Core to manage incoming data messages and provide data-driven services and applications. A testbed was carried out in a real house in the city of Valparaiso, Chile, over a one-year period, where four appliances were used to collect energy consumption using smart plugs, as well as collecting the main energy load of the house through a data logger acting as a smart meter. To the best of our knowledge, this is the first electrical energy dataset with a 10-second sampling rate from a real household in Valparaiso, Chile. Results show that both implementations perform the baseline tasks (collecting, storing, and controlling) for a HEMS. This work contributes by providing a detailed technical implementation of HEMS that enables researchers and engineers to develop and implement HEMS solutions to support different smart home applications.

In-Situ Cure Monitoring of Wind Turbine Blades by Using Fiber Bragg Grating Sensors and Fresnel Reflection Measurement.

A fiber-optic cure monitoring system is proposed to measure curing status of composite structure such as a large scale wind turbine blade. The monitoring is based on the measurement of Fresnel reflectivity at the optical fiber/epoxy resin interface. The refractive index of epoxy resin varies throughout curing stages, changing the Fresnel reflectivity. The curing status is decided by monitoring the reflected intensity variation. The usage of fiber Bragg grating (FBG) sensor helps to separate the temperature-induced cross effects. A Gaussian curve fitting algorithm was applied to FBG spectra which were distorted in curing procedure. The substantial measurement errors could be minimized by locating the centroids of the Gaussian curve-fitted spectra. From the experiments performed in various isothermal conditions, the proposed system successfully identified the onset of gelation and the completion of curing of epoxy resins.

A self-referencing intensity-based fiber optic sensor with multipoint sensing characteristics.

A self-referencing, intensity-based fiber optic sensor (FOS) is proposed and demonstrated. The theoretical analysis for the proposed design is given, and the validity of the theoretical analysis is confirmed via experiments. We define the measurement parameter, X, and the calibration factor, ß, to find the transfer function, , of the intensity-based FOS head. The self-referencing and multipoint sensing characteristics of the proposed system are validated by showing the measured and relative error versus the optical power attenuation of the sensor head for four cases: optical source fluctuation, various remote sensing point distances, fiber Bragg gratings (FBGs) with different characteristics, and multiple sensor heads with cascade and/or parallel forms. The power-budget analysis and limitations of the measurement rates are discussed, and the measurement results of fiber-reinforced plastic (FRP) coupon strain using the proposed FOS are given as an actual measurement. The proposed FOS has several benefits, including a self-referencing characteristic, the flexibility to determine FBGs, and a simple structure in terms of the number of devices and measuring procedure.

Reconfigurable routing protocol for free space optical sensor networks.

Recently, free space optical sensor networks (FSOSNs), which are based on free space optics (FSO) instead of radio frequency (RF), have gained increasing visibility over traditional wireless sensor networks (WSNs) due to their advantages such as larger capacity, higher security, and lower cost. However, the performance of FSOSNs is restricted to the requirement of a direct line-of-sight (LOS) path between a sender and a receiver pair. Once a node dies of energy depletion, the network would probably suffer from a dramatic decrease of connectivity, resulting in a huge loss of data packets. Thus, this paper proposes a reconfigurable routing protocol (RRP) to overcome this problem by dynamically reconfiguring the network virtual topology. The RRP works in three phases: (1) virtual topology construction, (2) routing establishment, and (3) reconfigurable routing. When data transmission begins, the data packets are first routed through the shortest hop paths. Then a reconfiguration is initiated by the node whose residual energy falls below a threshold. Nodes affected by this dying node are classified into two types, namely maintenance nodes and adjustment nodes, and they are reconfigured according to the types. An energy model is designed to evaluate the performance of RRP through OPNET simulation. Our simulation results indicate that the RRP achieves better performance compared with the simple-link protocol and a direct reconfiguration scheme in terms of connectivity, network lifetime, packet delivery ratio and the number of living nodes.

A cross-layer duty cycle MAC protocol supporting a pipeline feature for wireless sensor networks.

Although the conventional duty cycle MAC protocols for Wireless Sensor Networks (WSNs) such as RMAC perform well in terms of saving energy and reducing end-to-end delivery latency, they were designed independently and require an extra routing protocol in the network layer to provide path information for the MAC layer. In this paper, we propose a new cross-layer duty cycle MAC protocol with data forwarding supporting a pipeline feature (P-MAC) for WSNs. P-MAC first divides the whole network into many grades around the sink. Each node identifies its grade according to its logical hop distance to the sink and simultaneously establishes a sleep/wakeup schedule using the grade information. Those nodes in the same grade keep the same schedule, which is staggered with the schedule of the nodes in the adjacent grade. Then a variation of the RTS/CTS handshake mechanism is used to forward data continuously in a pipeline fashion from the higher grade to the lower grade nodes and finally to the sink. No extra routing overhead is needed, thus increasing the network scalability while maintaining the superiority of duty-cycling. The simulation results in OPNET show that P-MAC has better performance than S-MAC and RMAC in terms of packet delivery latency and energy efficiency.

Investigation on reliability and scalability of an FBG-based hierarchical AOFSN.

The reliability and scalability of large-scale based optical fiber sensor networks (AOFSN) are considered in this paper. The AOFSN network consists of three-level hierarchical sensor network architectures. The first two levels consist of active interrogation and remote nodes (RNs) and the third level, called the sensor subnet (SSN), consists of passive Fiber Bragg Gratings (FBGs) and a few switches. The switch architectures in the RN and various SSNs to improve the reliability and scalability of AOFSN are studied. Two SSNs with a regular topology are proposed to support simple routing and scalability in AOFSN: square-based sensor cells (SSC) and pentagon-based sensor cells (PSC). The reliability and scalability are evaluated in terms of the available sensing coverage in the case of one or multiple link failures.

A novel kind of programmable 3(n) feed-forward optical fiber true delay line based on SOA.

A new kind of 3(n) feed-forward programmable optical fiber true delay line was proposed. Theoretical analysis was presented on its delay performance and expandability. Experimental demonstration was given to show the implementation of such delay lines using SOAs and Farady rotation mirrors. Delay step as small as 0.5 ps with precision of about 0.03 ps was achieved. Measurement was performed to verify the feasibility and results are given.