2017 International Conference on Signals and Systems (ICSigSys), 2017
Energy harvesting has become very attractive due to the extended usage time of devices. Among sev... more Energy harvesting has become very attractive due to the extended usage time of devices. Among several forms of recycling energy, radiofrequency (RF) harvesting has been suggested due to its wide availability mainly in urban areas. Its applications range from sensor nodes to charging low power consumption portable devices and depend on the amount of antennas. In this paper, we evaluate the feasible application of RF harvesting for charging a cell phone. To validate our analysis, we conduct an RF measurement campaign at four important locations in Brasilia, Brazil. Considering the average incidence of 11 dBm, we achieve the final value of 2.5 mW/m2. With an incident power of +10 dBm, only 2 rectennas per hour are needed to charge a cell phone whose battery is approximately 3.72 mWh. We perform a comparison between rectenna arrays and simple antennas directly connected to one external matching circuit, dismissing adaptive beamforming circuits as a way of avoiding intermediate energy losses. In order to apply RF energy harvesting in higher power consumption devices, we propose a rectenna array system which increases considerably the amount of recycled power. For both Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) paths, harvesting systems based on rectenna arrays outperform standard antenna array based solutions.
2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), 2019
Drones or unmanned aerial vehicles (UAV) are remotely piloted aircrafts which are very popular fo... more Drones or unmanned aerial vehicles (UAV) are remotely piloted aircrafts which are very popular for commercial and public-safety applications. However, they can impose several security threats such as espionage and terrorism-related activities. In this way, we propose a multidimensional antenna array based framework in order to accurately localize UAVs in multipath environments. Specifically, we extend a previous framework for signal emitter localization in two aspects: (i) by adopting a tensor representation to better exploit the structure inherently multidimensional of the data, and (ii) by including a multiple denoising preprocessing scheme to increase the signal-to-noise ratio of the received signal. Numerical results show that the proposed approach presents both lower position coordinate errors and spatial frequency errors when compared to the matrix-based and tensor-based techniques with spatial smoothing as denoising preprocessing step.
2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2016
Electricity demand time series are stochastic processes related to climate, social and economic v... more Electricity demand time series are stochastic processes related to climate, social and economic variables. By predicting the evolution of such time series, electrical load forecasting can be performed in order to support the electrical grid planning. In this paper, we propose a Kalman based load forecasting system for daily demand forecasting. Our proposed approach incorporates a Principal Component Analysis (PCA) of the input variables obtained from linear and nonlinear transformations of the candidate time series. In order to validate our predicting scheme, data collected from Brasília distribution company has been used. Our proposed approach outperforms state-of-the-art approaches based on state space and artificial neural networks.
2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), 2019
Protecting sensitive information is an increasingly difficult task due to the advances in hardwar... more Protecting sensitive information is an increasingly difficult task due to the advances in hardware. Brute force attacks (BFA) have been successful in accessing protected data. As BFA is a trial and error process, and a natural solution against it consists of enhancing the range of possible secret values. One of the most used cryptographic techniques to protect sensitive data is the Secret Sharing Scheme (SSS), by means of which one can protect the secret by mathematically and individually distributing it into shares over n participants. Only when a minimal quantity of t participants combine their shares the secret is revealed to all of them. Among the several applications of the Chinese Remainder Theorem (CRT), it is also used as a SSS. Although the state-of-the-art Asmuth-Bloom’s SSS is perfect in terms of secrecy, the candidate values for the secret are quite small, therefore enhancing the probability of a successful BFA, as less values are to be tested by the attacker. In this pa...
Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also produc... more Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also producers, smart grids have become a key solution for electricity infrastructure. In smart grids, one of the most crucial requirements is the privacy of the final users. The vast majority of the literature addresses the privacy issue by providing ways of hiding user’s electricity consumption. However, open issues in the literature related to the privacy of the electricity producers still remain. In this paper, we propose a framework that preserves the secrecy of prosumers’ identities and provides protection against the traffic analysis attack in a competitive market for energy trade in a Neighborhood Area Network (NAN). In addition, the amount of bidders and of successful bids are hidden from malicious attackers by our framework. Due to the need for small data throughput for the bidders, the communication links of our framework are based on a proprietary communication system. Still, in terms o...
2017 International Conference on Signals and Systems (ICSigSys), 2017
Energy harvesting has become very attractive due to the extended usage time of devices. Among sev... more Energy harvesting has become very attractive due to the extended usage time of devices. Among several forms of recycling energy, radiofrequency (RF) harvesting has been suggested due to its wide availability mainly in urban areas. Its applications range from sensor nodes to charging low power consumption portable devices and depend on the amount of antennas. In this paper, we evaluate the feasible application of RF harvesting for charging a cell phone. To validate our analysis, we conduct an RF measurement campaign at four important locations in Brasilia, Brazil. Considering the average incidence of 11 dBm, we achieve the final value of 2.5 mW/m2. With an incident power of +10 dBm, only 2 rectennas per hour are needed to charge a cell phone whose battery is approximately 3.72 mWh. We perform a comparison between rectenna arrays and simple antennas directly connected to one external matching circuit, dismissing adaptive beamforming circuits as a way of avoiding intermediate energy losses. In order to apply RF energy harvesting in higher power consumption devices, we propose a rectenna array system which increases considerably the amount of recycled power. For both Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) paths, harvesting systems based on rectenna arrays outperform standard antenna array based solutions.
2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), 2019
Drones or unmanned aerial vehicles (UAV) are remotely piloted aircrafts which are very popular fo... more Drones or unmanned aerial vehicles (UAV) are remotely piloted aircrafts which are very popular for commercial and public-safety applications. However, they can impose several security threats such as espionage and terrorism-related activities. In this way, we propose a multidimensional antenna array based framework in order to accurately localize UAVs in multipath environments. Specifically, we extend a previous framework for signal emitter localization in two aspects: (i) by adopting a tensor representation to better exploit the structure inherently multidimensional of the data, and (ii) by including a multiple denoising preprocessing scheme to increase the signal-to-noise ratio of the received signal. Numerical results show that the proposed approach presents both lower position coordinate errors and spatial frequency errors when compared to the matrix-based and tensor-based techniques with spatial smoothing as denoising preprocessing step.
2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2016
Electricity demand time series are stochastic processes related to climate, social and economic v... more Electricity demand time series are stochastic processes related to climate, social and economic variables. By predicting the evolution of such time series, electrical load forecasting can be performed in order to support the electrical grid planning. In this paper, we propose a Kalman based load forecasting system for daily demand forecasting. Our proposed approach incorporates a Principal Component Analysis (PCA) of the input variables obtained from linear and nonlinear transformations of the candidate time series. In order to validate our predicting scheme, data collected from Brasília distribution company has been used. Our proposed approach outperforms state-of-the-art approaches based on state space and artificial neural networks.
2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS), 2019
Protecting sensitive information is an increasingly difficult task due to the advances in hardwar... more Protecting sensitive information is an increasingly difficult task due to the advances in hardware. Brute force attacks (BFA) have been successful in accessing protected data. As BFA is a trial and error process, and a natural solution against it consists of enhancing the range of possible secret values. One of the most used cryptographic techniques to protect sensitive data is the Secret Sharing Scheme (SSS), by means of which one can protect the secret by mathematically and individually distributing it into shares over n participants. Only when a minimal quantity of t participants combine their shares the secret is revealed to all of them. Among the several applications of the Chinese Remainder Theorem (CRT), it is also used as a SSS. Although the state-of-the-art Asmuth-Bloom’s SSS is perfect in terms of secrecy, the candidate values for the secret are quite small, therefore enhancing the probability of a successful BFA, as less values are to be tested by the attacker. In this pa...
Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also produc... more Due to the drastic increase of electricity prosumers, i.e., energy consumers that are also producers, smart grids have become a key solution for electricity infrastructure. In smart grids, one of the most crucial requirements is the privacy of the final users. The vast majority of the literature addresses the privacy issue by providing ways of hiding user’s electricity consumption. However, open issues in the literature related to the privacy of the electricity producers still remain. In this paper, we propose a framework that preserves the secrecy of prosumers’ identities and provides protection against the traffic analysis attack in a competitive market for energy trade in a Neighborhood Area Network (NAN). In addition, the amount of bidders and of successful bids are hidden from malicious attackers by our framework. Due to the need for small data throughput for the bidders, the communication links of our framework are based on a proprietary communication system. Still, in terms o...
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Papers by Jayme Milanezi