Intelligent M2M Network using Healthcare...
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Intelligent M2M Network using Healthcare Sensors Seung Hwan Shin, Rossi Kamal, Rim Haw, Seung Il Moon, Choong Seon Hong Kyung Hee University, Korea Email: (shshin,rossi,rhaw,simoon)@networking.khu.ac.kr,[email protected] Mi Jung Choi Kangwon National University,Korea Email:[email protected] Abstract—Machine to Machine (M2M), communication be- tween the machines without or with the least-human involvement, is going to be an important part of life. Healthcare is one of the areas on which M2M is going to play major roles. At present time, healthcare sensors monitor patient information and notify remote doctors. However, if we can integrate more intelligence in healthcare sensors, then these can sense patient’s emergency condition by themselves and can notify doctor before severe condition. In this context, we have developed intelligent mobile sensor agents in a healthcare scenario in a M2M context. This sensor agent can sense blood pressure of a patient and can notify remote doctor, with the help of an intelligent adapter and a manager in a M2M healthcare scenario. I. I NTRODUCTION 1 M2M[1]stands for the intelligent communication between machines without or with the least involvement of human. With the penetration of intelligent smart-devices and sensors, M2M is going to be an important factor of daily life. M2M has expanded its usages in different areas. Healthcare is one of the important usage models those have taken great interest in these days. With the inclusion of smart-devices and body-sensors, healthcare is forwarded to a new direction[1] M2M devices, especially body sensors are, deployed in vital sign monitoring of patients[2]. This monitoring information is sent to remote doctor who can take clinical decision on the patient. However, if sensors are given intelligence, they can determine the condition of patient by itself and can inform the remote doctor in proper time[3][4]. An agent is a software program that can take decision in an autonomous way[5]. An agent sensor node can adapt to changing networking condition and can perform intelligent tasks. Hence, a sensor agent can be very helpful for the healthcare environment in a M2M scenario[5][6][7]. We are developing a policy-based autonomic managment software for M2M network and services(Fig. 1). The major goal is to manage M2M network in an autonomic way so that software can learn environmental context and can adapt to changing environment. Manager, mobile sensor agent and adapters are major functional componets of this autonomic software. The role of manager is to store policies according to which it can take decision on monitoring information. The role of adapter is to behave intelligent way so that it can take 1 This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency)" (NIPA-2011-(C1090-1121-0003)) decision by itself or take assistance from manager. The role of mobile sensor agent is to adapt to the changing environmental context. As healthcare is an emerging field, we are motivated to develop intelligent adapter and mobile sensor agent in a healthcare scenario of M2M networks. So, we have developed intelligent sensor agent(Fig. 1) and adapter(Fig. 1) for M2M communication in a healthcare scenario. Depending on the patient condition, sensor agent can change communication and sensing interval and can notify remote doctor through intelligent and scalable adapter. Our contribution is as follows (a)Development of a mobile sensor agent that can change communication and processing interval. (b)Development of an intelligent and scalable adapter. In- telligent means that it can take help of manager if it needs, else it takes decision itself. Scalable means that it can support different types of healthcare sensors, including 6LoWPAN, Zigbee etc. (c)We have considered sensor-agent and an adapter in a healthcare scenario when a patient’s blood pressure sensor agent notifies remote doctor, through an intelligent adapter. (d)We have implemented mobile sensor agent and adapter in HyBus c2430 heathcare sensors with sensing attributes blood pressure, temperature, pulse oximetry and heart-rate. This paper is organized as follows:Section II presents the motivation of our research work. We have presented our proposal with architecture, algorithm and application scenario in section III. We have discussed implementation results in section IV. At last, we have concluded in section V. II. MOTIVATION FOR I NTELLIGENCE IN M2M IN HEALTHCARE SCENARIO In this section, we have elaborated our research motivation for the intelligence in M2M in a healthcare scenario Research on M2M[1] has focused on providing intelligence on machine, so that there is little or no human involvement. M2M is concerned with smart-devices and ubiquitous sensors, those are deployed in monitoring in different use-cases like smart-grid, vehicular communication, healthcare. With the huge penetration of smart-devices in recent times, we envision a future when enormous M2M data will be exchanged among intelligent devices. The key research issue is how we can manage this huge data in an intelligent way and how we can provide energy efficiency in those devices[1] Heathcare sensor networks[3] have opened new horizon for healthcare with its contribution in both wearable and in-vivo forms. Now-a-days they are deployed in monitoring of patients
Transcript of Intelligent M2M Network using Healthcare...
Intelligent M2M Network using Healthcare SensorsSeung Hwan Shin, Rossi Kamal, Rim Haw, Seung Il Moon, Choong Seon Hong
Kyung Hee University, KoreaEmail: (shshin,rossi,rhaw,simoon)@networking.khu.ac.kr,[email protected]
Mi Jung ChoiKangwon National University,Korea
Email:[email protected]
Abstract—Machine to Machine (M2M), communication be-tween the machines without or with the least-human involvement,is going to be an important part of life. Healthcare is one of theareas on which M2M is going to play major roles. At presenttime, healthcare sensors monitor patient information and notifyremote doctors. However, if we can integrate more intelligencein healthcare sensors, then these can sense patient’s emergencycondition by themselves and can notify doctor before severecondition. In this context, we have developed intelligent mobilesensor agents in a healthcare scenario in a M2M context. Thissensor agent can sense blood pressure of a patient and can notifyremote doctor, with the help of an intelligent adapter and amanager in a M2M healthcare scenario.
I. INTRODUCTION
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M2M[1]stands for the intelligent communication betweenmachines without or with the least involvement of human.With the penetration of intelligent smart-devices and sensors,M2M is going to be an important factor of daily life.
M2M has expanded its usages in different areas. Healthcareis one of the important usage models those have taken greatinterest in these days. With the inclusion of smart-devices andbody-sensors, healthcare is forwarded to a new direction[1]
M2M devices, especially body sensors are, deployed in vitalsign monitoring of patients[2]. This monitoring information issent to remote doctor who can take clinical decision on thepatient. However, if sensors are given intelligence, they candetermine the condition of patient by itself and can informthe remote doctor in proper time[3][4].
An agent is a software program that can take decision inan autonomous way[5]. An agent sensor node can adapt tochanging networking condition and can perform intelligenttasks. Hence, a sensor agent can be very helpful for thehealthcare environment in a M2M scenario[5][6][7].
We are developing a policy-based autonomic managmentsoftware for M2M network and services(Fig. 1). The majorgoal is to manage M2M network in an autonomic way sothat software can learn environmental context and can adaptto changing environment. Manager, mobile sensor agent andadapters are major functional componets of this autonomicsoftware. The role of manager is to store policies accordingto which it can take decision on monitoring information. Therole of adapter is to behave intelligent way so that it can take
1This research was supported by the MKE(The Ministry of KnowledgeEconomy), Korea, under the ITRC(Information Technology Research Center)support program supervised by the NIPA(National IT Industry PromotionAgency)" (NIPA-2011-(C1090-1121-0003))
decision by itself or take assistance from manager. The role ofmobile sensor agent is to adapt to the changing environmentalcontext. As healthcare is an emerging field, we are motivatedto develop intelligent adapter and mobile sensor agent in ahealthcare scenario of M2M networks. So, we have developedintelligent sensor agent(Fig. 1) and adapter(Fig. 1) for M2Mcommunication in a healthcare scenario. Depending on thepatient condition, sensor agent can change communicationand sensing interval and can notify remote doctor throughintelligent and scalable adapter. Our contribution is as follows
(a)Development of a mobile sensor agent that can changecommunication and processing interval.
(b)Development of an intelligent and scalable adapter. In-telligent means that it can take help of manager if it needs,else it takes decision itself. Scalable means that it can supportdifferent types of healthcare sensors, including 6LoWPAN,Zigbee etc.
(c)We have considered sensor-agent and an adapter in ahealthcare scenario when a patient’s blood pressure sensoragent notifies remote doctor, through an intelligent adapter.
(d)We have implemented mobile sensor agent and adapter inHyBus c2430 heathcare sensors with sensing attributes bloodpressure, temperature, pulse oximetry and heart-rate.
This paper is organized as follows:Section II presents themotivation of our research work. We have presented ourproposal with architecture, algorithm and application scenarioin section III. We have discussed implementation results insection IV. At last, we have concluded in section V.
II. MOTIVATION FOR INTELLIGENCE IN M2M INHEALTHCARE SCENARIO
In this section, we have elaborated our research motivationfor the intelligence in M2M in a healthcare scenario
Research on M2M[1] has focused on providing intelligenceon machine, so that there is little or no human involvement.M2M is concerned with smart-devices and ubiquitous sensors,those are deployed in monitoring in different use-cases likesmart-grid, vehicular communication, healthcare. With thehuge penetration of smart-devices in recent times, we envisiona future when enormous M2M data will be exchanged amongintelligent devices. The key research issue is how we canmanage this huge data in an intelligent way and how we canprovide energy efficiency in those devices[1]
Heathcare sensor networks[3] have opened new horizon forhealthcare with its contribution in both wearable and in-vivoforms. Now-a-days they are deployed in monitoring of patients
Fig. 1. Proposed Policy-based Autonomic Management Architecture
of critical diseases like dementia, Alzheimer [2] or diagnosisprocess of internal blood circulation, artificial retina in human[3]. In M2M perspective, the key research issue is how wecan provide more intelligence in those body sensors thosecan provide self-management, self-configuration, data-featureextraction etc[2][4].
Mobile agent[5] is a software program installed in sensornodes that can assist that node to adapt to the changingenvironmental context. The key research issue on mobile agenthas been how we can manage mobile sensor agents in anautonomic way by providing as much intelligence on it [6].Other issues are how we can manage autonomic communica-tion between mobile sensor agent and gateway, how we canprovide intelligent communication among the sensor agentsthemselves[7].
In this context, we have been motivated to use mobile agentsin healthcare sensors to provide more intelligence in M2Mcommunication in a healthcare scenario.
III. PROPOSAL OF MOBILE SENSOR AGENT AND ADAPTERFOR INTELLIGENT M2M COMMUNICATION IN
HEALTHCARE SCENARIO
In this section, we describe architecture, functionality andapplication scenario of proposed intelligent M2M networkwith healthcare sensors.
A. Architecture
We propose mobile sensor agent and adapter for imple-menting intelligent M2M network(Fig. 1). Fig. 1 shows thearchitecture of mobile sensor agent and adapter, respectively.Fig. 2 shows data flow between each modules of agent andadapter. Red flow represents transmission data flow frommanager to agent and blue flow represents sensed data flowfrom agent.
1) Mobile Sensor Agent: Mobile sensor agent(Fig. 1) con-sists of three modules including sensing, processing, and com-munication. Sensing module senses physiological informationlikes blood pressure, heart beat, and blood oxygen level usingsensors. Processing module applies received policy data from
Fig. 2. Data flow between Mobile Sensor Agent and Adapter
Fig. 3. Healthcare sensors used in implementation (a)temperature Sensor(b)pulse oximeter sensor (c)blood pressure sensor (d)ekg sensor
adapter. Communication module sends sensed data to adapterand receives policies from adapter.
2) Adapter: Adapter(Fig.1) consists of modules includingcommunication, processing, local decision point, and forward-ing and light-weight DB. Communication module receivessensed data from agent and sends adapter’s command to agent.Processing module processes the sensed data received fromagent and prepares policy which agent has. Local decisionpoint decides the command for agent by preparing policyusing data which processing module processed. Forwardingmodule can forward the sensed data receiving from adapter tomanager when adapter does not have appropriate policies tohandle monitoring information of sensor agent. Light-weightDB is the policy repository of adapter.
B. Functionality
We have proposed separate algorithms for the intelligentmobile sensor agent and intelligent and scalable adapter ina M2M Healthcare scenario. Intelligence of Mobile sensoragent (Algorithm 1) yields that if patient’s vital sign is
Algorithm 1 Intelligence of Mobile Sensor Agent1. if sensed value is NORMAL then2. senses with NORMAL interval3. sends sensed info to Adapter in NORMAL interval.4. end if5. if sensed value is ABNORMAL then6. senses with LESS interval7. sends sensed info to Adapter in LESS interval.8. end if
Algorithm 2 Scalability of Adapter1. if sensor with sensing attribute X arrives then2. create thread for sensor with X sensing attribute.3. end if4. if sensor with protocol Y arrives then5. create thread for Y protocol(6LowPAN, Zigbee,
MIC etc.)6. end if
NORMAL, the healthcare sensor can notify monitoring dataafter NORMAL interval. Mobile sensor agent does not needto change sensing or processing interval. However, if the vitalsign of patient is changed abnormally, mobile sensor agentneeds to reduce sensing and communicatio interval to notifyadapter frequently.
Scalability of Adapter(Algorithm 2) yields that adapter canrecognize healthcare sensors of different sensing attributesor different protocols (6LowPAN, Zigbee). Intelligence ofAdapter (Algorithm 3) yieds that adapter at first tries todeal sensed info of agents. If adapter’s local policy suits torange of sensed info, adapter processes sensed info with localdecision point and local database. Otherwise, adapter forwardmonitoring info of patient to manager and waits for furtherprocessing form manager.
Figure 2 shows data flows between each module in adapter.In this way, we minimize human intervention by givingintelligence to adapter to decide action by oneself dependingon patient status.
C. Application Scenario
We have summarized the application scenario in Fig. 4. Weassume the situation that healthcare sensor agents are installedwith a patient(Fig.3). Each healthcare sensor agent sensespatient’s physiological information(blood pressure, heartbeat,blood oxygen level and etc.) and transmits to adapter installedat home. Adapter keeps policies for received data from agent.If adapter doesn’t have appropriate policy which matchescontext of received data, it requests new policy to manager[1]and applies that. Adpater then notifies the patient status toremote doctor.
IV. IMPLEMENTATION DETAILS
In this section, we have discussed our experience of mobilesensor agent and adapter implementation on FreeRTOS oper-ating system on 6LowPAN-based healthcare sensor nodes.
Fig. 4. Mobile Sensor Agent, Adapter and Manager are deployed in themonitoring of Blood Pressure Patient in a Healthcare Scenario
TABLE IVARIABLE TYPES
Type Size DescriptionAgendID 2 A unique identifier for each agent
Type 2 Type of dataReading 4 Sensed data
Value 4 Command
TABLE IIFUNCTIONS USED IN ADAPTER
Communication sendToAdapterAgent(), receiveFromAgent()Processing messageHandle()
Local Decision Point preparePolicy(),makeCommand()Forwarding sendToManager(),receiveFromManager
TABLE IIIFUNCTIONS IN MOBILE SENSOR AGENT
Communication sendToAdapter(), receiveFromAdapter()Processing chagePolicy()
Sensing sensing()
TABLE IVOPERATORS USED IN IMPLEMENTATION
Identifier Description< Less than≤ Less than or equal to> Greater than≥ Greater than or equal to+ Add− Substract== Equal to! = Not Equal to
Algorithm 3 Intelligence of Adapter1. if Available configuration policy suits to sensed value
then2. locally decide about monitoring info with local
decision point and local database3. end if4. if Available configuration policy does not suit to sensed
value then5. forward monitoring info to the Manager.6. end if
A. Hardware
In our experiement, adapter is implemented on PC. Mobilesensor agent is implemented on Hmote2430 on Hybus[10]based cc2430, one chip solutions of Texas Instruments. Fig. 3shows our used healthcare sensor nodes with sensing attributes(Pulse oximetry, infrared thermometer, EKG, temperature).
B. Software
Adapter and sensor agent program is written on C languageusing Nanostack API on FreeRTOS operating system. We havemodified 2430bs and 2430client programs of Nanostack APIfor adapter and sensor agent programs, respectively.
C. Experiments
In our experiment, we have used specific message for-mat(Table I) and operators(Table IV) for the communicationbetween mobile sensor agent and adapter. We also havesummaraized the functions developed for adapter and mobilesensor agent programs in Table II and III respectively.
Adapter first waits for the sensing information from mo-bile sensor agents(Fig. 5). Mobile sensor agent then sensesphysiological sign. It then sends that physiological sign to theadapter.At last, adapter receives monitoring information fromthe mobile sensor agent.
D. Software Testing Experience
In our experiments, communication between sensor agentand adapter is halted for some unidentified reasons. Debuggingsensor program in computer prior to embedded implementa-tion might enhance the quality of the work.
V. CONCLUSION
In this paper, we have proposed mobile sensor agent andadapter towards intelligent M2M communication in health-care scenario. We have implemented our adapter and mobilesensor agent program in C2430 HyBus healthcare sensormotes[11][12] and experimented thier performance with test-results[13].
REFERENCES
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Fig. 5. Adapter is receiving sensed info of patient
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