Internet of things applications for smart cities

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Introduction

• IoT technologies and principles hold the promise of being able to improve the resource management of many assets related to city life, including the flow of goods, the movement of private and public vehicles, and the greening of the environment.

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• When cities deploy on a broad scale state-of-the-art Information and Communication Technologies (ICT), including, in particular, IoT technologies, they are referred to as being “smart cities.”

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• Smart cities application areas include but are not limited to intelligent transportation systems, smart grids, smart buildings, goods and products, logistics, sensing , surveillance/intelligence, and smart services.
• Cities have been incorporating new technologies over the years, but recently the rate of technology adoption has increased, especially for, but not limited to, surveillance, traffic control, energy efficiency, and street lighting.
• Smart cities do not depend on any specific or unique IoT technology, but include all forms of IoT technologies, including appropriate sensors, appropriate networks, and appropriate analytics, all of which may depend on the particular vertical application under consideration.

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• IoT-based multimedia (IoTMM) applications.
• Two new research-oriented results for IoT deployment in smart cities environments:

(1) The support of multimedia-oriented IoT applications, for example, for public safety and surveillance applications and

(2) The application of the family of Mobile IPv6 (MIPv6) protocols for mobility-based applications, for example, for vehicular crowdsensing.

• Mobility and mobility management are underlying requirements of many smart city applications.

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IoT Applications for Smart Cities

• Cities are now constantly challenged “to do more with less”.
• while managing costs indeed, many city challenges can be addressed or at least ameliorated by IoT principles.
• Livability, infrastructure and real estate management, traffic transportation and mobility, logistics, electric power and other city-supporting utilities, and security are perhaps the key aspects of a city from a substratum perspective.
• Drones (a type of IoT device) will also play a role in many smart city applications.

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• The following four trends are seen as important by city planners:

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(i) Demographic and workforce trends.

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(ii) Infrastructure cost and financing.

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(iii) The growth of public and private mobility systems.

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(iv)The availability of new modes of transportation.

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• Naturally, not all challenges faced by cities can be completely solved by IoT solutions—such IoT solutions basically provide data on resources (e.g., power usage), data on state (e.g., traffic), data on logistics (e.g., movement of goods), data on security (e.g., surveillance), and the ability to deliver advanced smart services (e.g., smart parking meters.)

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Specific Smart City Applications

• Driverless Vehicles.
• Crowdsensing.
• Smart Buildings.
• Smart Campuses.
• Smart Grid.

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Driverless Vehicles.

• Advances in wireless communication techniques and location-aware sensor technologies are fueling the evolution of vehicle networks (VNs).
• One might see a significant expansion of autonomous transportation in fleet vehicles such as commercial trucks. Fleets are the initial area where driverless vehicle technology is expected to be widely deployed.
• The U.S. National Highway Traffic Safety Administration has defined five levels of vehicle automation based on how active the driver is during operation.

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• Level 0—No Automation.

The operator is in control of all aspects of the vehicle’s functions at all times, although the vehicle may have features that passively warn the driver of a potential collision or lane departure. IoT applications: basic internal in-vehicle monitoring of functionality.

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• Level 1—Function-Specific Automation.

The operator is in full control of the vehicle, but may use automated features that can affect control speed, braking or steering to assist with specific functions (cruise control, automatic braking, and lane keeping systems). IoT applications: more advanced internal in vehicle monitoring of functionality.

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• Level 2—Combined Function Automation.

Automation allows the operator to be disengaged forsome portions of the trip (e.g., the driver may be able to take his or her hands off the wheel and foot off the pedal), but the operator must still actively monitor the vehicle and be ready to take control at any time. IoT applications: internal in-vehicle monitoring of functionality in conjunction with onboard/off board signaling to detect environmental conditions.

• Level 3—Limited Self-Driving Automation.

The operator no longer needs to be constantly monitoring the roadway, since the vehicle handles critical safety functions under certain conditions, while alerting the operator if there is an upcoming obstacle. IoT applications: advanced onboard/off board signaling to detect environmental conditions.

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• Level 4—Full Self-Driving Automation.

The operator no longer has any responsibility for safe operation of the vehicle, and is not expected to monitor road conditions or take control at any point during the trip. IoT applications: complete and exhaustive onboard/offboard signaling to detect environmental conditions.

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Crowdsensing

• Crowdsensing allows a large population of mobile devices to measure phenomena of common interest over an extended geographic area, enabling “big data” collection, analysis, and sharing.
• It has major urban applications for the (active or passive) collection of traffic conditions, weather conditions, and even video images.
• Crowdsensing can be a major technical enabler to address the challenges associated with the urban-based paradigm shift discussed earlier.
• Crowdsensing entails massive collection of data and often the (geo)location of that data (i.e., location of the [mobile] sensor where the data is being collected) for aggregation and analysis. The term mobile crowdsensing (MCS) has been coined to describe a broad set of crowdsensing applications.

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• In recent years, the widespread availability of sensor-provided smartphones has enabled the possibility of harvesting large quantities of data in urban areas exploiting user devices, thus enabling a suite of urban crowdsensing applications.
• Since on-board power is generally less of an issue for crowdsensing sensors, IPv6 protocols and MIPv6 mobility management techniques may be a useful technology to conside.

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Smart Buildings

• Many of the applications for smart cities have applicability to building management; some of these applications include video surveillance, traffic/access control, surveillance, energy management (including lighting), indoor environmental and air quality/comfort control, and fire detection, among others.

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• Heating, Ventilation, and Air Conditioning (HVAC) Room. modular boilers, air compressors, and chillers.
• Server Room. uninterruptible power supplies (UPSs); computer room air conditioners (CRACs); telecom closets; racks and virtualized/blade servers.
• Office Space. light-emitting diodes (LEDs) lighting; daylight sensors; thermostats (used in controlling HVAC systems and energy consumption); demand response mechanisms.
• Cooling System Elements. rooftop units (RTUs), cooling towers, and heat pumps

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• In aggregate (across all commercial buildings), the

key electrical energy consumption elements are as follows:

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Cooling: 14.9%

Ventilation: 15.8%

Lighting 17.1%

Refrigeration: 15.8%

Office equipment: 4.1%

Computers 9.5%

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• Building management systems(BMSs)
• BMS have traditionally been used to manage several building-related functions. It is a computerized platform that allows for monitoring and controlling a building’s mechanical and electrical equipment.
• Typically used to manage loads and enhance efficiency, thus reducing the energy needed to illuminate, heat, cool, and ventilate a building.
• BMSs interact with controls hardware in the various mechanical/ electrical subsystems for real-time monitoring and controlling of the energy used.
• Although current-generating BMSs typically focus primarily on electrical consumption, in the future BMSs are expected to cover all energy sources supporting a building, also including natural gas, renewable energy, water usage, and steam systems.

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Smart Campuses

• A campus is typically comprised of several buildings under one administrative jurisdiction, such as a (private) university or college, or a hospital complex encompassing several structures in a small geographic area.
• The applications that are typically considered for smart campus are somewhat more limited. These might include external campus surveillance; internal surveillance; building emergency generator, automatic transferswitch (ATS), and digital meter monitoring and control; elevator monitoring and control; and HVAC monitoring and control. Other campus-related applications include remote door control, water leak detection, washing machine scheduler, smart parking, smart trash cans, light control, and emergency notification

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• Energy efficiency and conservation are becoming more important, especially considering governmental mandates in many jurisdictions to reduce energy consumption by 20% by 2020 or 2025; IoT-based capabilities can facilitate the achievement of these goals.
• The smart building IoT applications (for example, occupancy, lighting, daylight harvesting, access control, fire safety, and so on) can also be considered to be part of smart campus applications.
• For campus wireless IoT connectivity, typically, one can make use of license-free industrial, scientific, and medical (ISM) bands.
• While a number of such bands exist, the ISM unlicensed radio band at 900 MHz (specifically at 902–928 MHz) is often optimally employed due to better weather-related performance and the reduced congestion from Wi-Fi and other devices (operating in the 2.4 or 5 GHz bands);900 MHz also supports “long distance links” that can span several miles.

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• Traditional spread spectrum techniques, where a radio signal generated with a particular bandwidth is by design spread in the frequency domain into a signal with a much wider bandwidth, will also reduce the interference (however, spread spectrum system are slightly more expensive than normal transmitter– receivers.)
• Other bands available include the V-band (40 to 75 GHz) and the E-band (60 to 90 GHz);
• Can substitute for physical fiber over short distances (of a few miles)
• Typically they support wireless Gigabit Ethernet in metropolitan areas

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Smart Grid

• Smart cities benefit from being served by smart grids (SGs).
• The SG is an evolution of the electricity network that integrates the activities of power consumers, power generators, distribution grid, and devices connected to the grid (e.g., substations, transformers, etc.).
• The goal of SG is to economically and efficiently deliver sustainable, reliable, and secure electricity supplies.
• The reliable and cost-effective delivery of power is obviously critical to cities; thus, SGs support the smart city paradigm.
• These wireless technologies range from unlicensed local (the so-called fog) connectivity to licensed 3G/4G/ 5G cellular to low earth orbit (LEO) satellites. All of these technologies are relevant to the SG.

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• Utilities have started to gradually support M2M and Supervisory Control And Data Acquisition (SCADA) systems over wireless and satellite links; these connectivity technologies are applicable to the SG for city and rural environments.
• A SG encompasses the various stages of power generation, distribution, and consumption. The goal is to exploit the power of automation to better control distribution, green efficiency, and consumption. SG management technologies are needed to address these and related power management issues.
• Three basic issues are of interest: monitoring of rural transmission systems, demand response (DR) support, and urban automated meter readers (AMRs).

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• Well known examples of IoT usage in energy efficiency and interactions with the SG/AMI include the following:

Smart thermostats; smart appliances that can interwork with DR-based SG power management.

“plug-level” control of electrical outlets, where lower end devices can be turned on or off remotely

IoT-based LED lighting and daylight sensors for “smart lighting” that not only allow intelligent centralized (and/or remote) control but also lower energy consumption while improving the residents’ experience; and, consumers’ ability to generate green renewable power and sell it back to the SG.

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Smart Connected Homes

• A smart connected home is an instance of this paradigm, inheriting all the aspects of connectivity of the involved devices.
• A smart connected home is a residence equipped with sensors, systems, and devices that can be remotely accessed, controlled, and monitored, typically via the Internet.
• Latest progress includes, in particular, integration platforms, new stakeholders, increased usage of cloud services, voice-controlled devices, and widespread availability of sensor technologies in modern everyday appliances.

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Concept of Smart Connected Home

• There is no commonly accepted definition of the smart connected home, but in general, a smart home may denote any kind of residence (e.g., apartment cottage, and rented living space), which involves information and Communication technologies allowing for remote control, monitoring, and access.
• Smart home needs to have ambient intelligence and automatic control allowing it to recognize and possibly make decisions on its own guided by the behavior of the residents.

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• Smart home includes systems that allow the residents to operate home appliances, typically only locally from within the house. This type of smart home tends to rely on wireline-based standards such as KNX and it is not connected to the Internet. Commonly, it tends to focus on the automation of lighting, windows, and in-house entertainment, and is associated with building automation.
• Connected home allows for remote control and management of appliances, typically over IP-based networks (e.g., the Internet). Additionally, this type of home usually provides services that promote and support, for example, security, health care, and energy management. Moreover, this type of house generally includes a central hub (gateway) from which the system can be controlled together with a user interface that can be operated typically through a smartphone.

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• Smart connected home includes functionality from both previous types, but also adds communication and service-exchange between related areas, such as the grid and electric vehicle and on-site microgeneration (e.g., rooftop solar panels) Smart connected homes thus merge the functionality from both the connected home and the smart home. It may also include system capabilities, such as learning, prediction of, and response to the occupants’ needs and lifestyle preferences in their home environment.

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Smart Connected Home Stakeholders

• In IoT applications, such as smart homes or smart buildings, there are diverse stakeholders ranging from technology investors, technology developers, technology integrators, and more.
• Device Manufacturers.
• Service Providers.
• Network Providers.
• Regulators.
• Platform Providers.
• End Users.

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Smart connected home systems

• Smart connected home systems can be organized into four categories as systems that support energy, entertainment, health care, or security services.

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Energy

Energy systems are targeted to provide efficient energy consumption and management for the home. The energy domain commonly involves the use of smart meters, smart thermostats, and adaptive lighting systems. System architectures in this domain may utilize “intelligent” multiagent systems and control strategies to predict and automatically maximize energy efficiency and user comfort.

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Entertainment

Smart connected home systems tend to promote entertainment typically maximizing occupants’ comfort and convenience by providing personalized amusement content and social communication services. The entertainment sector commonly involves game consoles, connected TVs, and smart speaker systems.

Health Care

• The health care service area is focused on providing mobile health care and fitness support, and aims to provide independent healthy living.
• The health care service also involves the use of wearable sensors (e.g., wrist straps) in order to allow for possibly continuous monitoring of body signal parameters (e.g., cardiac diseases) even while not at home. Health care services can monitor the residents’ personal health, generate tailored health reports, and may support remote diagnoses and chronic disease management.

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Security

• The security domain is one of the main motivations for consumers to purchase smart home systems,16 despite the various privacy concerns related to in-house video surveillance.
• Smart connected homes security systems are especially popular among residents living in towns where there are reports of high criminal activities. However, their widespread adoption is also linked to the convenience factor being offered by such systems. Furthermore, it can be noted that this domain is tightly linked to surveillance systems, involving technologies such as cameras and motion sensors that are predominantly used in intelligent buildings.

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Internet of Things in Smart Ambulance and Emergency Medicine

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• Various data collected by biosensors with varying volumes can be further analyzed for diagnosis and prognosis of chronic diseases. As health care service providers become increasingly reliant on intelligent and interconnected devices in every aspect of health support, critical reliability, data integrity, and interoperability are important considerations that need to be thoroughly addressed.
• Data analytics and syndromic surveillance for providing effective treatment in remote rescue entail careful consideration from data acquisition, selection, transmission, mining, analysis all the way to manipulation and storage to update electronic patient records (EPR) as well as disease database maintenance.

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• It is in fact possible to eliminate the need for transporting the patient to the hospital after providing necessary relief, thereby reducing the demand on hospital accident and emergency (A&E) personnel.
• One of the key challenges of designing a smart ambulance is the confined space limitation of the vehicle itself, very limited space is available for additional equipment.

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IoT in Emergency Medicine

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Point-of-Care Environment

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• Vital signs if a patient that may indicate the mortality of a patient such that no treatment remains meaningful.
• Oxygen administration with SpO2 measurement below 94% for identification of high risk patients.
• Respiratory determination of type and severity.
• Cardiac conditions with ECG in the diagnosis of anterior ST elevation myocardial infarction (STEMI) as well as other conditions such as cardiac arrest and atrial fibrillation or flutter.
• Shock and trauma entails image processing engines and determining causes of hypovolemia. The former allows fast and accurate diagnosis of burns severity, spinal cord injury, joint dislocation, and fracture misalignment; whereas the latter may involve mechanism for fluid loss detection or infrared sensing for hyperthermia patients.
• Metabolic analysis involves protection of frontline paramedics’ personal safety; this concerns agitated delirium in case a patient exhibits sign of anxiety with physical aggression.

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• Capturing, aggregating, filtering, and sharing data from health systems seamlessly into emergency medicine is both a challenge and promise of the Medical IoT, where IoT serves as the point where patient data are directly linked to the national health care system via telemedicine. IoT allows monitoring in remote and demanding locations through the smart ambulance as a hub. Data filtering and aggregation in the ambulance gateway facilitates full duplex data transfer and storage to the hospital.

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Biosensing Network

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• Biosensors form the basic building blocks of IoT in emergency medicine that drives the development of biocompatible composite materials and the design of reliable biosensing networks using novel composite materials .
• In order to maximize biosensors’ reliability, the sensor head should be encapsulated in a cavity to avoid interference from external sources.
• The primary consideration here is optimizing cavity creation and the method of actuating the sensor head inside the cavity from the interaction between encapsulation and the biological parameters to be measured.
• The wireless biosensing system consists of a network of environmental biosensors that have minimal space requirements. The embedded micro electro mechanical system (MEMS) is mounted with an adequate degree of freedom to oscillate during use since it may be subject to surface stress and analyte interaction.

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• Heat sensing biosensors commonly found in emergency medicine.
• For improved reliability, thermistors can be used to monitor any changes in ambient temperatures while measurement is taken.
• One major advantage of using IoT in the ambulance is the ability of supporting self-calibration.
• Environmental awareness is extremely important in reliability assurance through condition-based monitoring.

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Hierarchical Cloud Architecture

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• Integrating the biosensing network into an ambulance setting, a hierarchical cloud platform model for context-aware emergency support services would be useful to control both resources and scheduling by supporting a range of context-aware IoT services in the cloud control layer (CCL)
• The main advantage is to control each context-aware service for the patient and the paramedic in the user control layer (UCL).

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