RFID-based Object Detection System in IoT

RFID-based Object Detection System in IoT

Mohammad Ali Safvati - Ali Soleymani Iranians University (An e-Institute of Higher Education) Tehran, Iran ABSTRACT Abstract – RFID (radio frequency identification) is an important technology which is used to detect and identify objects. Considering that in the near future (and even today) all real things can connect with each other over the internet, so one of the significant prerequisites in the combination model is unique identification over the internet. This paper, which will be done with the goal of integrations between RFID and IoT, and briefly cloud computing, introduce components and implementation idea for this model. In addition will present current issues and challenges for this convergence. Keywords: RFID, Internet of Things, Convergences

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INTRODUCTION

By providing of the internet of things by Kevin Ashton in 1999, a great change appears in technology which has a direct effect in our lifestyle. smart cities, smart home, medical care, traffic rules and etc. are examples of IoT. In this model, real objects could connect with each other over the internet. With every new technology, other technologies and other integrations will be appearing which could create a more efficient model. An important point in IoT is object detection and uniqueness. A hybrid model that is discussed in this article is integration between RFID, as an important identification tools with the wireless sensor network, and its convergence with IoT and cloud computing. In addition, related issues and challenges are considered and some solutions are represented. This article consists of three parts. In The first part, the concept of the Internet of Things, its architecture, applications, technologies, various communication, and sensor types are discussed. In the second part, an overview on wireless sensor networks and RFID is presented. Finally, convergence between RFID and WSN, Internet of Things and cloud computing is studied. Internet of Things (IoT) which is described by the ITU 1, is a dynamic heterogeneous infrastructure that within it every object has a connection with each other’s and send data for processing and also communicate their capabilities cross over the internet. Everything needs three basic parameters: identification, sensors, and connections. Via these parameters, the things identified by an Identifier like RDIF or can sense events of surroundings via sensors (wearable, implanted, and environmental) and with connections, those can transfer sensed data to Intelligent central Processing units like cloud computing, fuzzy recognition, and other intelligent computing technology [1]. In many several articles, different IoT architectures are represented. Here, after summing up, an open model of IoT diagram or architecture shown in Table 1 [2-6] :

Service layer Edge layer Access gateway

TABLE 1. THE MODELS OF IoT ENVIRONMENT All information which captured by technologies of sensors,WSN,RFID,GPS. Providing data transmission in core network by GSM,WIMAX or it is the backbone of every information. Including application services. Including hardware equipment such as sensors , RFID tags. Including data handling in platform communication like message routing.

Middleware layer

An interface between hardware layer and application layer.

Application layer

Delivering distinct application.

Perception layer Network layer

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International Telecommunications Union

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Internet of things uses Internet standards to provide optimized services for management information [6]. The important technologies in IoT are RFID systems, Sensor networks, and intelligence models. As an example in Smart Planet, sensors are inserted within objects or systems so that they can communicate to create an intelligent architecture. IoT uses wearable sensors in personal Smart-Health systems to produce and manage medical knowledge. By putting up wireless sensors inside the home or clothes and other items, personal health diagnosis is possible. Smart-Health systems cloud provide the best solution in order to detect and heal dangerous behavioral anomalies. Not only the above but also IoT sensors can be useful in cars for detecting a driver’s operation, or for reminding the owner of the suitcase and thousands another examples [3]. Some of the challenges of IoT are power consumption, cost and object identification in integrated circuits or wireless communications. Therefore these factors improve utilizing a sensor network and include intelligent sensors for enabling, processing and analyzing of valuable information [6]. 2.

WIRELESS SENSOR NETWORK 2.1 IoT Sensor Node

Sensor nodes are physical miniature devices which consist of seven components: sensor, DC-DC, ADC, battery, MCU, memory, and radio transceiver (Fig. 1). They could sense or gather information from the objects behaviors and environment by the analog signals and communicate in specific geographic areas for example target tracking or monitoring.

Fig. 1. sensor diagram Battery or power source: provides the energy (electricity) for operation of the node. DC-DC: the device that catchs entrance voltage and generates DC voltage which is different from primitive voltage. this is used for noise separating. Sensors: the device which can sense. ADC: is analog to digital converter. MCU 2 : is central processing unit for each node. Radio: is the device in the node which receives the control signal from the sender and sends the operator data from the sensors to the base station or cluster head. Memory : local storage is stationed which typically log data to a Compact Flash card or hard drive [7]. Sensors are used in a wide range of applications due to following advantages: reliability, accuracy, flexibility, cost-effectiveness, and ease of deployment. The advancements and convergence of MEMS 3 technology, wireless communications, and digital electronics Sensors are the results of using sensors. These sensors which are called nodes in the network, like every technology, have some challenges such as limited memory, difficult-to-access locations, battery or power supply (limited energy) [4, 6, 8]. IoT sensors are classified into two categories: 1 - Wired sensor: In this type power source is wired and the data transceiver is using wired communication. Because of wired technology, sensors are highly reliable but their applications are limited and the topology is complex. 2- Wireless sensor: In this type, the nodes are not connected with any wire. Transceivers wirelessly send /receive the data and control signals to/from the control unit, These sensors don’t have problems with wired sensors [9]. The set of sensors make a network which are called sensor networks. These networks have its specific protocols, and standards. In this network and based on its architecture, the data move between sensors to the base station or cluster head for processing or analyzing goals. They are classified to three models [4, 8]: • • •

continuous model: the sensors transfer their data continuously. event-driven data model: the sensors report information only if an event occurs. request-reply model: this is a hybrid model and the sensors report their results in response to an explicit request from the reporter.

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Micro Control Unit

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Micro-Electro-Mechanical Systems

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There are various sensors for sensing different things. Temperature, pressure, humidity, gesture, touch sensors, are examples of various sensors which are common in their application. Table 2 briefly shows the common sensors and their applications [4, 10].

Sensor Pressure Sensor

TABLE 2. INTRODUCE TYPE OF SENSORS AND APPLICATIONS Description Example detecting pressure around the earth or another LPS25H pressure sensor from environment ST-Microelectronics is used for GPS-based navigation.

accelerometer

is used to detect vibration, tilt, and linear acceleration

gyroscope

is used to measure angular velocity

Temperature sensor

It is used to control the performance of the IoT device at varied temperatures

Humidity sensor

is used to control performance of the device

Proximity sensor

Silicon Labs' optical sensor family enables sensing UV Index, ambient light, long range proximity, heart rate/pulse oximetry and motion with 2D or 3D gestures.

Touch sensor

are used as capacitive touch sense applications

It is used for implementation of a pedometer ,leveling, vibration alert,anti-theft and more. used in 3D mouses, games and athlete training. ADT7320 is a digital temperature sensor with a range from -40 degree to +150 degree. HTU21D from Measurement Specialties is digital humidity sensor, NPA-700, Si70xx Si114x, Si1132, Si1120, and Si1102 are sensors from Silicon Labs used as infrared proximity sensors. sliders, wheels, touch buttons, liquid level sensing and capacitive proximity sensing.

There are five major parameters that are important and effective on sensor performance: Energy efficiency: for obtaining maximum system lifetime energy consumption of sensors, This energy feed by the battery. Latency: given delay about the phenomena must be clear for the observer. Accuracy: accurate information is the primary objective for a reporter. There is a trade-off between accuracy, latency and energy efficiency. Fault-tolerance: sensors may fail due to physical conditions or their energy runs out or data replication. Scalability: it is a critical factor for large-scale networks, It is likely that localizing interactions through hierarchy and aggregation will be critical for ensuring scalability [8]. 2.2 WSN concepts As mentioned before, a set of sensors create a network which one of them could sense environment behaviors and transfer data to their headquarters, This communication performs by wire or wireless technologies. In this section, wireless sensor network (WSN), concepts, different types, applications and challenges are discussed. Generally, WSN is made up of a large number of sensors which are deployed to collaborate for monitoring and analyzing a phenomenon. It is the perfect choice for the design and deployment of next-generation monitoring and control systems. The communication between sensors done via an infrastructure, ad-hoc or hybrid wireless mode. By using WSN, researchers and scientists use typical data station consist of a group of massive and heavy components that are difficult to move and may require car batteries for power or often require vehicle or helicopter assistance for equipment installation and maintenance. In comparison with the wired sensor network, WSN has many advantages such as low cost, easy installation and maintenance , good stability and failure rate of connectors , continuous, high-resolution, ubiquitous sensing, mobility, redundancy and the lowest easy level of the energy consumption[5, 7, 11]. The components that make up the WSN monitoring network described in Fig. 2:

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Fig. 2. WSN components According to Fig. 2 three components make WSN: hardware, communication, middleware. Hardware consists of sensor components which is previously explained in the sensor section, communication shows how data transfers to database base on related topology and architecture. Finally, middleware is a mechanism which mixes an infrastructure with a SOA 4 to provide access to heterogeneous sensor resources for developing sensor applications [5, 12, 13]. There are some applications in this networks such as real-time monitoring of air quality by means of unattended stations or smart construction which improve living conditions to reduce energy consumption. Healthcare monitoring that is possible to ensure patients continuous monitoring, also used to detecting the oilfields on the seafloor, hazardous environment exploration and seismic sensing like Volcanic tomography in geophysics community. Depending on types of environments, WSNs are deployed on land, underground (is used for monitoring underground conditions), underwater (sensors is deployed underwater and transfer data from acoustic waves), terrestrial (consists of many of wireless sensor nodes deployed in a fixed area), multi-media (sensor nodes equipped with cameras and microphones to monitors events in the form of multimedia such as video, audio, and imaging) and mobile WSN [7, 8]. 2.3 GLOBAL WIRELESS TECHNOLOGIES This section introduces some important and common wireless technologies which are used in the network layer of IoT architecture. The goal of these technologies are data transmission to the central point. Briefly, the sensor senses data from environment and transfer them from an interface or an infrastructure base on mentioned protocols in Table III protocols [1, 5, 9]. TABLE 3. IoT WIRELESS TECHNOLOGY Wireless Specifications Comments technology ZigBee IEEE:802.15.4Low-cost wireless network technology, short delay and provides 868,915,MHz,2.4GHz faster response, is reliable data transfer since it uses a dynamic routing protocol, is used to continuously monitor the parameter 20kbps,40kbps, 250kbps data of the greenhouse. EnOcean ISO/IEC:14543-3-10 uses direct media access control (MAC) scheme, which reduces 902,928 MHz, 125 the message collision probability and hence saves energy avoiding Kbps the repetition of message several times use the normal reliability. Waves ETS 300-220 - 868, ultra low power energy consumption, long range transmission of a 915, 433 MHz small amount of data, easy network device setup. 4.8 to 100 100 Kbps Z-wave ITU-T - 915MHz - 40 designed for remotely controlled applications, reach is up to 30 kbps meters in the air and reduced indoor. Wi-Fi Bluetooth NFC

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IEEE 802.11 11Mbps-300Mbps 2400-2483.5 MHz 1000-3000Kbps ISO/IEC 18000 13.56 MHz - 106-424 Kbps

used in home networks. makes a network of maximum 7 nodes and network called piconet. Is a set of communication protocol that enables two electronic devices one of which usually portable like smartphone.

Service Oriented Architecture

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6LoWPAN

3.

IEEE 802.15.4 - 1 – 2.4 GHz 20-250 Kbps

is a communication technology that enables connectivity of the hardware limited devices (sensors, actuators, etc.) onto IPv6 network.

RADIO FREQUENCY IDENTIFICATION

RFID is equipped by some readers which could establish a person’s interaction or detect changes of the chemical/physical parameters against the environment. These applications help IoT to improve their benefits such as taking care of the human health-state or manufacturing, agriculture management, health care and medicine, military and defense, payment transactions, environment monitoring and disaster warning and other applications which have effective impacts in our life like time saving, operating cost saving. however an important point that must be considered is supplying standardization for encoding information over RFID tag in UPC 5 system which are used in the electronic transactions between companies [6, 14-16]. Attentive to all advantages in this technology, but there are some issues and challenges which could create a risk like memory and power limitations, unreliable communication and security requirements. With an overview, the first item must consider that it is not easy to reduce the size of the code of a security algorithm and know the replacement of nodes to gain energy of sensors. Second, unreliable communication leads to network security violation because of security attacks[10, 17]. There are many factors which have impacts in RFID, these factors are categorized in three sections: performance, security and communication, each category has its destructive effects; for example, in communication, angle of rotation, distance, noisy signals, electromagnetic interference that leads to collisions and scattering or shadowing effects that caused by the human body may be consequences. In security, unprotected tags may be vulnerable to eavesdropping or spoofing or denial of service which are factors that threaten safety. In the following, lack of standardization of protocols at the hardware and software levels, tag placement, tags stability, accuracy, along with other factors which already discussed, affect the performance.[2, 12, 18] 3.1 RFID Components RFID systems are made up of three main components: RFID tags (transmitters-responders), the reader (transmitters/receivers) and application system (middleware) which are in active or passive mode. In passive mode, RFID systems use tags with no internal power source and feeds by electromagnetic energy transmitted from a RFID reader but in Active model RFID systems uses battery-powered RFID tags [19]. It should be noted that various articles represented different models for RFID, for example, They inserted an antenna in components as it used for transmitting and receiving radio waves for communication but with a summing up, Three main components which previously said are classified [2, 6, 14, 18, 20]. Tags: it is an identifier for objects in the format of microchip that connect to an antenna and has a unique identification number (ID) and memory that stores additional data such as the manufacturer name, product type. Readers: it can communicate with the tags by using radio waves without line-of-sight to read/write data in the tags. It is a powerful device with large memory and computational resources. Middleware: by middleware, data are connected to enterprise application system for processing and analyzing. 4.

RFID’S CONVERGENCES

This section to demonstrates how RFID and WSN are combined and how they can integrate with IoT and cloud computing. At first, for example, object tracking which are used in movement vehicles such as trucks or cars is considered. by using RFID, objects could have tracked or identified for evaluating their performances or detecting the precise location. First, objects equipped with embedded tags that communicate with RFID reader, then the RFID reader’s broadcasts a signal through an antenna to transponders like a computer system for collecting, logging and processing. The transponder receives signals and evaluate the objects behavior. Fig. 3 shows these processes.

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Universal Product Code

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Fig. 3. RFID tag and Reader relation. This paper speaks about IoT and the integration between sensing and tracking technologies. So an environment is necessary for data distributing, here the internet as a public infrastructure will be used. Now some questions are considered, how data transfer from RFID to analyzers over the internet? how does RFID make a connection with clouds environment? and how it could make a connectivity with wireless sensor network or another network or another model? These question are described in the following section. 4.1 Combining RFID and WSN It can be assumed that the RFID is a kind of cheaper sensor that has developed in parallel method with WSN to gain more information about the environment. RFID is used for identifying and WSN is used for sensing. In this scheme, RFID is attached to the object to sense temperature, PH value, vibrational and so on. The sensed information is transmitted between tags via available WSN combination protocols and send it to local PC or remote LAN via an integrated smart base station. For example, this type of application is useful for museums where the RFID reader is integrated with the camera, and tags are attached to the objects in the museum. After the object is sensed, RFID can provide additional information about the object. This integration works in software layer because RFID and WNS work separately in hardware format [21]. Power consumption is a serious problem in this integration. For overcoming this problem, some solutions such as using ZigBee protocol or lessening the nodes power consumption by putting them to sleep mode while they are inactive are considered [22]. 4.2 RFID and IoT convergence The IoT needs an ability for uniquely identifying things and this is critical for the development of IoT. Therefore, in some papers it is mentioned that RFID is a prerequisite for the IoT because objects are controlled via the Internet. IoT and RFID standards are improving together simultaneously. The identification and authentication are the main reasons of installing RFID. This technology can track and capture data automatically in intelligence devices and send them to the resource planning systems for data-mining[3, 18]. Resource systems with SOA concepts in IoT application could create RFID web services which can connect to outside services and implement data collecting and exchange in the group of heterogeneous webs. As an example, search engines for things are sample of web-based RFID application which returns data or logs that are stored by tags in databases so users or researchers could search and observe their requests [23]. This convergence could represent a new schema like RFID components which already is discussed. In the new scheme one part is added and it is the tag manager. It can store and manage information about the tags in a repository and an important capability of tag manager is the two-way connectivity to the Internet [19]. Moreover, this operation could perform by connecting a smartphone with RFID tags or smartphone with readers. First, a smartphone with a RFID tag can connect to GSM or another wireless phone network and attach a RFID chip with some identification information. Second, a smartphone with a RFID reader is connected to the wireless phone network and contains a RFID reader that can collect data from diverse of RFID tags. This model has an advantage because cellular telecommunication operators are hugely popular [24]. This combination must considers the difference between two paradigms: addressing and identification. Identification refers to the name of objects like “X object” which are not globally unique but provides a clear identity for each object. Addressing refers to its address within a communication network by using IPs to uniquely identify objects. Fig. 4 clearly shows the routing of a message from the corresponding node to the tag [18].

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Fig. 4. Address updating Some PCs are integrated with sensors and network functionalities which are typically used to realize IoT products. The implementation of this convergence can use the IoT layer structure that was explained in IoT section. There are some software and hardware platforms which developed IoT technology , Arduino, UDOO, Friendly ARM, Intel Galileo, Raspberry PI, Gadgeteer, BeagleBone, Cubieboard, Z1, WiSense, Mullen, and T-Mote Sky in hardware layers and the Contiki RTOS 6 in software Layers [25]. 4.3 RFID and Cloud convergence Cloud computing as an on-demand infrastructure provides access to all software or databases and etc. without installation. In this model user doesn’t need to spend costs for providing extra hardware but instead of that, they should be paid to cloud processor and use their services to improve calculation speeds, reduce peripheral costs and gain more secure and efficient systems [26]. A general view on RFID components and cloud computing can illustrate a new architecture. In this scheme, cloud replaced with the backend server. In this layout, a reader sends a signal to the cloud via network communication like mobile systems instead of backend server. Therefore, everybody could take advantage with considering access and authorization based on requirements [27]. As an implementation [26] exhibit a suitable example in a university environment. In this case, the student’s tag is passed by reader and students’ ID automatically update in the cloud platform system so the time of arrivals and departures is registered. CONCLUSIONS AND FUTURE WORKS This article has three purposes: how RFID could have identified objects and how sensors could sense the environment and finally how they could contact with the public infrastructures. IoT and cloud computing make a new integration model with RFID to provide easy access to the resources by users or researchers. As shown in fig. 5 probing in this field have increased during recent years. The blue line shows IoT and the red line shows RFID, Although RFID almost shows fixed path but IoT has positive progress. It should be considered that the development of hybrid models will be presented as a future work.

Fig. 5. Google Trends Results of RFID and IoT

In previous work shows how IoT and cloud computing could have a convergence to implement a strong environment for data processing or data storage with high accessibility and named it “ClouT”. As an applied view, Clout may combine with RFID to have another convergence model in future.

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Contiki has a simulator called Cooja which allows researcher and developers to simulate and emulate IoT and wireless sensor network (WSN) applications

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