Computer and Robot Vision Vol. 1, by R.M. Haralick and Linda G. Shapiro, Addison-Wesley, 1992, ISBN 0-201-10887-1.

Computer and Robot Vision

Recently, unmanned aerial vehicles (UAVs), or drones, have attracted a lot of attention, since they represent a new potential market. Along with the maturity of the technology and relevant regulations, a worldwide deployment of these UAVs is expected. Thanks to the high mobility of drones, they can be used to provide a lot of applications, such as service delivery, pollution mitigation, farming, and in the rescue operations. Due to its ubiquitous usability, the UAV will play an important role in the Internet of Things (IoT) vision, and it may become the main key enabler of this vision. While these UAVs would be deployed for specific objectives (e.g., service delivery), they can be, at the same time, used to offer new IoT value-added services when they are equipped with suitable and remotely controllable machine type communications (MTCs) devices (i.e., sensors, cameras, and actuators). However, deploying UAVs for the envisioned purposes cannot be done before overcoming the relevant challenging issues. These challenges comprise not only technical issues, such as physical collision, but also regulation issues as this nascent technology could be associated with problems like breaking the privacy of people or even use it for illegal operations like drug smuggling. Providing the communication to UAVs is another challenging issue facing the deployment of this technology. In this paper, a comprehensive survey on the UAVs and the related issues will be introduced. In addition, our envisioned UAV-based architecture for the delivery of UAV-based value-added IoT services from the sky will be introduced, and the relevant key challenges and requirements will be presented.

Low-Altitude Unmanned Aerial Vehicles-Based Internet of Things Services: Comprehensive Survey and Future Perspectives

Modern society faces serious problems with transportation systems, including but not limited to traffic congestion, safety, and pollution. Information communication technologies have gained increasing attention and importance in modern transportation systems. Automotive manufacturers are developing in-vehicle sensors and their applications in different areas including safety, traffic management, and infotainment. Government institutions are implementing roadside infrastructures such as cameras and sensors to collect data about environmental and traffic conditions. By seamlessly integrating vehicles and sensing devices, their sensing and communication capabilities can be leveraged to achieve smart and intelligent transportation systems. We discuss how sensor technology can be integrated with the transportation infrastructure to achieve a sustainable Intelligent Transportation System (ITS) and how safety, traffic control and infotainment applications can benefit from multiple sensors deployed in different elements of an ITS. Finally, we discuss some of the challenges that need to be addressed to enable a fully operational and cooperative ITS environment.

Sensor Technologies for Intelligent Transportation Systems.

Smart cities contain intelligent things which can intelligently automatically and collaboratively enhance life quality, save people's lives, and act a sustainable resource ecosystem. To achieve these advanced collaborative technologies such as drones, robotics, artificial intelligence, and Internet of Things (IoT) are required to increase the smartness of smart cities by improving the connectivity, energy efficiency, and quality of services (QoS). Therefore, collaborative drones and IoT play a vital role in supporting a lot of smart-city applications such as those involved in communication, transportation, agriculture,safety and security, disaster mitigation, environmental protection, service delivery, energy saving, e-waste reduction, weather monitoring, healthcare, etc. This paper presents a survey of the potential techniques and applications of collaborative drones and IoT which have recently been proposed in order to increase the smartness of smart cities. It provides a comprehensive overview highlighting the recent and ongoing research on collaborative drone and IoT in improving the real-time application of smart cities. This survey is different from previous ones in term of breadth, scope, and focus. In particular, we focus on the new concept of collaborative drones and IoT for improving smart-city applications. This survey attempts to show how collaborative drones and IoT improve the smartness of smart cities based on data collection, privacy and security, public safety, disaster management, energy consumption and quality of life in smart cities. It mainly focuses on the measurement of the smartness of smart cities, i.e., environmental aspects, life quality, public safety, and disaster management.

/pdf/survey-on-collaborative-smart-drones-and-internet-of-things-3xjk9xubzg.pdf

Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities

Radar in Meteorology

Crown fires are extremely dangerous, very difficult to fight and often have a rate of spread over 100 times more than a surface fire. Therefore, it is important to determine the type of forest fire in the early detection based on wireless sensor networks (WSNs) to adopt the proper strategy to fight the fire. It is shown that this could be done analyzing the noise power spectrum of forest fires: surface fires noise spectrum can be modeled as the red noise (gradual increase of trend line amplitude toward lower frequencies), while for crown fires noise spectrum trend line has an almost bell-shaped (Gaussian) type. The noise frequency range is relatively narrow for crown fires and ranged from 250 to 450 Hz. The intermediate type of fires (strong surface fire and incipient crown fire) has a transient noise spectrum from broadband red to narrowband Gaussian. The article presents the spectrums of 9 different forest fires. The different trend line of the forest fire noise power spectrum is the parameter that can be used to determine the type of forest fire in WSNs.

Spectral analysis of forest fire noise for early detection using wireless sensor networks

Quantitative precipitation estimation and rainfall monitoring based on meteorological data, potentially provides continuous, high-resolution and large-coverage data, are of high practical use: Think of hydrogeological risk management, hydroelectric power, road and tourism. Both conventional long-range radars and rain-gauges suffer from measurement errors and difficulties in precipitation estimation. For efficient monitoring operation of localized rain events of limited extension and of small basins of interest, an unrealistic extremely dense rain gauge network should be needed. Alternatively C-band or S-band meteorological long range radars are able to monitor rain fields over wide areas, however with not enough space and time resolution, and with high purchase and maintenance costs. Short-range X-band radars for rain monitoring can be a valid compromise solution between the two more common rain measurement and observation instruments. Lots of scientific efforts have already focused on radar-gauge adjustment and quantitative precipitation estimation in order to improve the radar measurement techniques. After some considerations about long range radars and gauge network, this paper presents instead some examples of how X-band mini radars can be very useful for the observation of rainfall events and how they can integrate and supplement long range radars and rain gauge networks. Three case studies are presented: A very localized and intense event, a rainfall event with high temporal and spatial variability and the employ of X-band mini radar in a mountainous region with narrow valleys. The adaptability of such radar devoted to monitor rain is demonstrated.

/pdf/x-band-mini-radar-for-observing-and-monitoring-rainfall-4qd135orv0.pdf

X-Band Mini Radar for Observing and Monitoring Rainfall Events

RIFD technologies are applied in a various number of environmental monitoring applications. Efficient energy management is one of the most important prerequisites for the realization of such systems and the power consumption of the RFID tag during radio transmissions must be kept low. The proposed system is composed by the RFID tags distributed on the territory and a reader installed on an Unmanned Aerial Vehicle (UAV). The idea is to use the UAV to collect data from the RFID sensors scattered throughout the area by simply approaching them, flying above them, and downloading measured data. This solution can be adopted to implement a grid of independent RFID sensors covering a large area, or to query sensors located in dangerous scenarios for humans. RFID tags are equipped with measuring sensors and store locally the measured parameters; the reader is mounted on the UAV and through an appropriate communication protocols it identifies the tags, downloads the data and sends them to the Ground Control Station (GCS). At the GCS a technician can control the reader through a GUI console: it is possible to start the discovery, download the sensor data (manually or automatically) and clear the RFID tags memory. An ad-hoc mechanisms has also been implemented to join fast tag discovery procedure, fast data downloading and energy saving. The present paper describes the system, presents the testing methodology and analyses some achieved performances in a test scenario.

/pdf/a-solution-for-monitoring-operations-in-harsh-environment-a-20dzawrl4p.pdf

A solution for monitoring operations in harsh environment: A RFID reader for small UAV

The paper presents the experimental implementation of a method to localize RFID tags in an outdoor environment using UAV. During the installation phase, it is possible to measure the coordinates of the installation point using a topographic GNSS receiver. The tags positions can evolve with time and after a specific desired period of time (e. g. 1 month or 1 year) it is necessary to relocate them. This can be done estimating the distance between the tags and a UAV, exploiting the measurements of the Received Signal Strength Indicator (RSSI). The tags are placed over an outdoor test area and a large amount of RSSI measurements are made in different position, well distributed in space, using a UAV equipped with a specific tag reader. On such data, a multilateration-based localization algorithm is applied achieving good results. The description of RFID tags is reported together with the localization algorithm, the test description and the preliminary results.

/pdf/localization-of-rfid-tags-for-environmental-monitoring-using-38wlgkeao7.pdf

Localization of RFID tags for environmental monitoring using UAV

Radar is a unique tool to get an overview on the weather situation, given its high spatio- temporal resolution. Over 60 years, researchers have been investigating ways for obtaining the best use of radar. As a result we often find assurances on how much radar is a useful tool, and it is! After this initial statement, however, regularly comes a long list on how to increase the accuracy of radar or in what direction to move for improving it. Perhaps we should rather ask: is the resulting data good enough for our application? The answers are often more complicated than desired. At first, some people expect miracles. Then, when their wishes are disappointed, they discard radar as a tool: both attitudes are wrong; radar is a unique tool to obtain an excellent overview on what is happening: when and where it is happening. At short ranges, we may even get good quantitative data. But at longer ranges it may be impossible to obtain the desired precision, e.g. the precision needed to alert people living in small catchments in mountainous terrain. We would have to set the critical limit for an alert so low that this limit would lead to an unacceptable rate of false alarms

/pdf/a-network-of-portable-low-cost-x-band-radars-3a6c5zqm2o.pdf

Silvano Bertoldo

Papers

Spectral analysis of forest fire noise for early detection using wireless sensor networks

X-Band Mini Radar for Observing and Monitoring Rainfall Events

A solution for monitoring operations in harsh environment: A RFID reader for small UAV

Localization of RFID tags for environmental monitoring using UAV

A Network of Portable, Low-Cost, X-Band Radars