I am very excited about the HCL Informix^® 15 external smartblob feature.

If you are not familiar with them, external smartblobs allow the user to store actual Binary Large Object (blob) and Character Large Object (clob) data external to the database. Metadata about that external storage is maintained by the database.

Notes: This article does NOT discuss details of the smartblobs feature itself, but rather proposes a solution to make the functionality more user-friendly. For details on feature behavior, setup, and new functions, see the documentation.

At the writing of this blog, v15.0 does not have the ifx_lo_path function defined, as required below.  This has been reported to engineering.  The workaround is to create it yourself with the following command:

create dba function ifx_lo_path(blob)
  returns lvarchar
  external name '(sq_lo_path)'
  language C;

This article also does not discuss details of client programming required to INSERT blobs and clobs into the database.

The external smartblob feature was built for two main reasons:

1. Backup size

Storing blobs in the database itself can cause the database to become extremely large. As such, performing backups on the database takes an inordinate amount of time, and 0 level backups can be impossible. Offloading the actual blob contents to an external file system can lessen the HCL Informix backup burden by putting the blob data somewhere else. The database still governs the storage of, and access to, the blob, but the physical blob is housed elsewhere/externally.

2. Easy access to blobs

Users would like easy access to blob data, with familiar tools, without having to go through the database. 

Using External Smartblobs in HCL Informix 15

HCL Informix 15 introduces external smartblobs. When you define an external smartblob space, you specify the external directory location (outside the database) where you would like the actual blob data to be stored. Then you assign blob column(s) to that external smartblob space when you CREATE TABLE. When a row is INSERTed, HCL Informix stores the blob data in the defined directory using an internal identifier for the filename.

Here’s an example of a customer forms table: custforms (denormalized and hardcoded for simplicity). My external sbspace directory is /home/informix/blog/resources/esbsp_dir1.

CREATE TABLE custforms(formid SERIAL, company CHAR(20), year INT, lname CHAR(20), 
formname CHAR(50), form CLOB) PUT form IN (esbsp);

Here, I INSERT a 2023 TaxForm123 document from a Java program for a woman named Sanchez, who works for Actian:

try(PreparedStatement p = c.prepareStatement("INSERT INTO custforms 
(company, year, lname, formname, form) values(?,?,?,?,?)");

FileInputStream is = new FileInputStream("file.xml")) {
p.setString(1, "Actian");
p.setString(2, "2023");
p.setString(3, "Sanchez");
p.setString(4, "TaxForm123");
p.setBinaryStream(5, is);
p.executeUpdate();
}

After I INSERT this row, my external directory and file would look like this:

[informix@schma01-rhvm03 resources]$ pwd
/home/informix/blog/resources
[informix@schma01-rhvm03 resources]$ ls -l esbsp*
-rw-rw---- 1 informix informix 10240000 Oct 17 13:22 esbsp_chunk1

esbsp_dir1:
total 0
drwxrwx--- 2 informix informix 41 Oct 17 13:19 IFMXSB0
[informix@schma01-rhvm03 resources]$ ls esbsp_dir1/IFMXSB0
LO[2,2,1(0x102),1729188125]

Where LO[2,2,1(0x102),1729188125]is an actual file that contains the data that I could access directly. The problem is that if I want to directly access this file for Ms. Sanchez, I would first have to figure out that this file belongs to her and is the tax document I want. It’s very cryptic!

A User-Friendly Smartblob Solution

When talking to Informix customers, they love the new external smartblobs feature but wish it could be a little more user-friendly.

As in the above example, instead of putting Sanchez’s 2023 TaxForm123 into a general directory called IFMXSB0 in a file called LO[2,2,1(0x102),1729188125, which together are meaningless to an end-user, wouldn’t it be nice if the file was located in an intuitive place like /home/forms/Actian/2024/TaxForm123/Sanchez.xml or something similar…something meaningful…how YOU want it organized?

Having HCL Informix automatically do this is a little easier said than done, primarily because the database would not intuitively know how any one customer would want to organize their blobs. What exact directory substructure? From what column or columns do I form the file names? What order? All use cases would be different.

Leveraging a User-Friendly Shadow Directory

The following solution shows how you can create your own user-friendly logical locations for your external smartblobs by automatically maintaining a lightweight shadow directory structure to correspond to actual storage locations. The solution uses a very simple system of triggers and stored procedures to do this.

Note: Examples here are shown on Linux, but other UNIX flavors should work also.

How to Set Up in 4 Steps

For each smartblob column in question

STEP 1: Decide how you want to organize access to your files.

Decide what you want the base of your shadow directory to be and create it. In my case for this blog, it is: /home/informix/blog/resources/user-friendly. You could probably implement this solution without a set base directory (as seen in the examples), but that may not be a good idea because users would unknowingly start creating directories everywhere.

STEP 2: Create a create_link stored procedure and corresponding trigger for INSERTs.

This procedure makes sure that the desired data-driven subdirectory structure exists from the base (mkdir -p), then forms a user-friendly logical link to the Informix smartblob file.    You must pass all the columns to this procedure from which you want to form the directory structure and filename from the trigger.

CREATE PROCEDURE

CREATE PROCEDURE create_link (p_formid INT, p_company CHAR(20), p_year INT,
p_lname CHAR(20), p_formname CHAR(50))

DEFINE v_oscommand CHAR(500);
DEFINE v_custlinkname CHAR(500);
DEFINE v_ifmxname CHAR(500);
DEFINE v_basedir CHAR(100);

-- set the base directory
LET v_basedir = '/home/informix/blog/resources/user-friendly';

-- make sure directory tree exists
LET v_oscommand = 'mkdir -p ' || TRIM(v_basedir) || '/' || TRIM(p_company) || '/' || 
TO_CHAR(p_year);
SYSTEM v_oscommand; 

-- form full link name 
LET v_custlinkname = TRIM(v_basedir) || '/' || TRIM(p_company) || '/' || TO_CHAR(p_year) 
|| '/' || TRIM(p_lname) || '.' || TRIM(p_formname) || '.' || TO_CHAR(p_formid);

-- get the actual location 
SELECT IFX_LO_PATH(form::LVARCHAR) INTO v_ifmxname FROM custforms WHERE formid = p_formid; 

-- create the os link 
LET v_oscommand = 'ln -s -f ' || '''' || TRIM(v_ifmxname) || '''' || ' ' || v_custlinkname; 
SYSTEM v_oscommand;

END PROCEDURE

CREATE TRIGGER

CREATE TRIGGER ins_tr INSERT ON custforms REFERENCING new AS post
FOR EACH ROW(EXECUTE PROCEDURE create_link (post.formid, post.company,
post.year, post.lname, post.formname));

STEP 3: Create a delete_link stored procedure and corresponding trigger for DELETEs.

This procedure will delete the shadow directory link if the row is deleted.

CREATE PROCEDURE

CREATE PROCEDURE delete_link (p_formid INT, p_company CHAR(20), p_year INT,
p_lname CHAR(20), p_formname CHAR(50))

DEFINE v_oscommand CHAR(500);
DEFINE v_custlinkname CHAR(500); 
DEFINE v_basedir CHAR(100);

-- set the base directory
LET v_basedir = '/home/informix/blog/resources/user-friendly';

-- form full link name
LET v_custlinkname = TRIM(v_basedir) || '/' ||
TRIM(p_company) || '/' || TO_CHAR(p_year) || '/' || TRIM(p_lname) || '.'
|| TRIM(p_formname) || '.' || TO_CHAR(p_formid);

-- remove the link
LET v_oscommand = 'rm -f -d ' || v_custlinkname;
SYSTEM v_oscommand;

END PROCEDURE

CREATE TRIGGER

CREATE TRIGGER del_tr DELETE ON custforms REFERENCING old AS pre FOR EACH ROW
(EXECUTE PROCEDURE delete_link (pre.formid, pre.company, pre.year, pre.lname, pre.formname));

STEP 4: Create a change_link stored procedure and corresponding trigger for UPDATEs, if desired.   In my example, Ms. Sanchez might get married to Mr. Simon and an UPDATE to her last name in the database occurs. I may then want to change all my user-friendly names from Sanchez to Simon.  This procedure deletes the old link and creates a new one.

Notice the update trigger only must fire on the columns that form your directory structure and filenames.

CREATE PROCEDURE

CREATE PROCEDURE change_link (p_formid INT, p_pre_company CHAR(20), 
p_pre_year INT, p_pre_lname CHAR(20), p_pre_formname CHAR(50), p_post_company CHAR(20), 
p_post_year INT, p_post_lname CHAR(20), p_post_formname CHAR(50))

DEFINE v_oscommand CHAR(500);
DEFINE v_custlinkname CHAR(500);
DEFINE v_ifmxname CHAR(500);
DEFINE v_basedir CHAR(100);
-- set the base directory
LET v_basedir = '/home/informix/blog/resources/user-friendly';

-- get rid of old

-- form old full link name
LET v_custlinkname = TRIM(v_basedir) || '/' || TRIM(p_pre_company) || '/' || 
TO_CHAR(p_pre_year) || '/' || TRIM(p_pre_lname) || '.' || TRIM(p_pre_formname) || '.' 
|| TO_CHAR(p_formid) ;

-- remove the link and empty directories
LET v_oscommand = 'rm -f -d ' || v_custlinkname;
SYSTEM v_oscommand;

-- form the new
-- make sure directory tree exists
LET v_oscommand = 'mkdir -p ' || TRIM(v_basedir) || '/' || TRIM(p_post_company) || '/' || 
TO_CHAR(p_post_year);
SYSTEM v_oscommand;

-- form full link name
LET v_custlinkname = TRIM(v_basedir) || '/' || TRIM(p_post_company) || '/' || 
TO_CHAR(p_post_year) || '/' || TRIM(p_post_lname) || '.' || TRIM(p_post_formname) 
|| '.' || TO_CHAR(p_formid) ;

-- get the actual location
-- this is the same as before as id has not changed
SELECT IFX_LO_PATH(form::LVARCHAR) INTO v_ifmxname FROM custforms WHERE formid = p_formid;

-- create the os link
LET v_oscommand = 'ln -s -f ' || '''' || TRIM(v_ifmxname) || '''' || ' ' || v_custlinkname;
SYSTEM v_oscommand;

END PROCEDURE

CREATE TRIGGER

CREATE TRIGGER upd_tr UPDATE OF formid, company, year, lname, formname ON custforms
REFERENCING OLD AS pre NEW as post

FOR EACH ROW(EXECUTE PROCEDURE change_link (pre.formid, pre.company, pre.year, pre.lname, 
pre.formname, post.company, post.year, post.lname, post.formname));

Results Example

Back to our example.

With this infrastructure in place, now in addition to the Informix-named file being in place, I would have these user-friendly links on my file system that I can easily locate and identify.

INSERT

[informix@schma01-rhvm03 2023]$ pwd

/home/informix/blog/resources/user-friendly/Actian/2023
[informix@schma01-rhvm03 2023]

$ ls Sanchez.TaxForm123.2

If I do an ls -l, you will see that it is a link to the Informix blob file.

[informix@schma01-rhvm03 2023]$ ls -l
total 0
lrwxrwxrwx 1 informix informix 76 Oct 17 14:20 Sanchez.TaxForm123.2 -> 
/home/informix/blog/resources/esbsp_dir1/IFMXSB0/LO[2,2,1(0x102),1729188126]

UPDATE

If I then update her last name with UPDATE custforms SET lname = ‘Simon’ where formid=2,my file system now looks like this:

[informix@schma01-rhvm03 2023]$ ls -l
lrwxrwxrwx 1 informix informix 76 Oct 17 14:25 Simon.TaxForm123.2 -> 
/home/informix/blog/resources/esbsp_dir1/IFMXSB0/LO[2,2,1(0x102),1729188126]

DELETE

If I then go and DELETE this form with DELETE FROM custforms where formid=2, my directory structure looks like this:

[informix@schma01-rhvm03 2023]$ pwd
/home/informix/blog/resources/user-friendly/Actian/2023
[informix@schma01-rhvm03 2023]$ ls
[informix@schma01-rhvm03 2023]$

We Welcome Your Feedback

Please enjoy the new HCL Informix15 external smartblob feature.

I hope this idea can make external smartblobs easier for you to use. If you have any feedback on the idea, especially on enhancements or experience in production, please feel free to contact me at mary.schulte@hcl-software.com. I look forward to hearing from you!

Find out more about the launch of HCL Informix 15.

Notes

1. Shadow directory permissions. In creating this example, I did not explore directory and file permissions, but rather just used general permissions settings on my sandbox server. Likely, you will want to control permissions to avoid some of the anomalies I discuss below.

2. Manual blob file delete. With external smartblobs, if permissions are not controlled, it is possible that a user might somehow delete the physical smartblob file itself from its directory. HCL Informix, itself, cannot control this from happening. In the event it does happen, HCL Informix does NOT delete the corresponding row; the blob file will just be missing. There may be aspects to links that can automatically handle this, but I have not investigated them for this blog.

3. Link deletion in the shadow directory. If permissions are not controlled, it is possible that a user might delete a logical link formed by this infrastructure. This solution does not detect this. If this is an issue, I would suggest a periodic maintenance job that cross references the shadow directory links to blob files to detect missing links. For those blobs with missing links, write a database program to look up the row’s location with the IFX_LO_PATH function, and reform the missing link.

4. Unique identifiers. I highly recommend using unique identifiers in this solution. In this simple example, I used formid. You don’t want to clutter things up, of course, but depending on how you structure your shadow directories and filenames, you may need to include more unique identifiers to avoid directory and link names duplication.

5. Empty directories. I did not investigate if there are options to rm in the delete stored procedure to clean up empty directories that might remain if a last item is deleted.

6. Production overhead. It is known that excessive triggers and stored procedures can add overhead to a production environment. For this blog, it is assumed that OLTP activity on blobs is not excessive, therefore production overhead should not be an issue. This being said, this solution has NOT been tested at scale.

7. NULL values. Make sure to consider the presence and impact of NULL values in columns used in this solution. For simplicity, I did not handle them here.

Informix is a trademark of IBM Corporation in at least one jurisdiction and is used under license.

The post User-Friendly External Smartblobs Using a Shadow Directory appeared first on Actian.

The need for securing data from unauthorized access is not new. It has been required by laws for handling personally identifiable information (PII) for quite a while. But the increasing use of data services in the cloud for all kinds of proprietary data that is not PII now makes data security an important part of most data strategies.

This is the start of a series of blog posts that take a detailed look at how data security can be ensured with Actian Vector. The first post explains the basic concept of encryption at rest and how Actian Vector’s Database Encryption functionality implements it.

Understanding Encryption at Rest

Encryption at rest refers to encryption of data at rest, which means data that is persisted, usually on disk or in cloud storage. This encryption can be used in a database system that is mainly user data in tables and indexes, but also includes the metadata describing the organization of the user data. The main purpose of encryption at rest is to secure the persisted data from unauthorized direct access on disk or in cloud storage, that is without a connection to the database system.

The encryption can be transparent to the database applications. In this case, encryption and decryption is managed by the administrator, usually at the level of databases. The application then does not need to be aware of the encryption. It connects to the database to access and work with the data as if there is no encryption at all. In Actian Vector, this type of encryption at rest is called database encryption.

Encryption at the application level, on the other hand, requires the application to handle the encryption and decryption. Often this means that the user of the application has to provide an encryption key for both, the encryption (e.g. when data is inserted) and the decryption (e.g. when data is selected). While more complicated, it provides more control to the application and the user.

For example, encryption can be applied more fine grained to specific tables, columns in tables, or even individual record values in table columns. It may be possible to use individual encryption keys for different data values. Thus, users can encrypt their private data with their own encryption key and be sure that without having this encryption key, no other user can see the data in clear text. In Actian Vector, encryption at the application level is referred to as function-based encryption.

Using Database Encryption in Actian Vector

In Actian Vector, the encryption that is transparent to the application works at the scope of a database and therefore is called database encryption. Whether a database is encrypted or not is determined with the creation of the database and cannot be changed later. When a database is created with database encryption, all the persisted data in tables and indexes, as well as the metadata for the database, is encrypted.

The encryption method is 256-bit AES, which requires a 32 byte symmetric encryption key. Symmetric means that the same key is used to encrypt and decrypt the data. This key is individually generated for each encrypted database and is called a database (encryption) key.

To have the database key available, it is stored in an internal system file of the database server, where it is protected by a passphrase. This passphrase is provided by the user when creating the database. However, the database key is not used to directly encrypt the user data. Instead, it is used to encrypt, i.e. protect, yet another set of encryption keys that in turn are used to encrypt the user data in the tables and indexes. This set of encryption keys is called table (encryption) keys.

Once the database is created, the administrator can use the chosen passphrase to “lock” the database. When the database is locked, the encrypted data cannot be accessed. Likewise, the administrator also uses the passphrase to “unlock” a locked database and thus re-enable access to the encrypted data. When the database is unlocked, the administrator can change the passphrase. If desired, it is also possible to rotate the database key when changing the passphrase.

The rotation of the database key is optional, because it means that the whole container of the table keys needs to be decrypted with the old database key to then re-encrypt it with the new database key. Because this container of the table keys also contains other metadata, it can be quite large and thus the rotation of the database key can become a slow and computationally expensive operation. Database key rotation therefore is only recommended if there is a reasonable suspicion that the database key was compromised. Most of the time, changing only the passphrase should be sufficient. And it is done quickly.

With Actian Vector it is also possible to rotate the table encryption keys. This is done independently from changing the passphrase and the database key, and can be performed on a complete database as well as on individual tables. For each key that is rotated, the data must be decrypted with the old key and re-encrypted with the new key. In this case, we are dealing with the user data in tables and indexes. If this data is very large, the key rotation can be very costly and time consuming. This is especially true when rotating all table keys of a database.

A typical workflow of using database encryption in Actian Vector:

• Create a database with encryption:

  1. 1. createdb -encrypt <database_name>

This command prompts the user twice for the passphrase and then creates the database with encryption. The new database remains unlocked, i.e. it is readily accessible, until it is explicitly locked or until shutdown of the database system.

It is important that the creator of the database remembers the provided passphrase because it is needed to unlock the database and make it accessible, e.g. after a restart of the database system.

• Lock the encrypted database:
  1. 1. Connect to the unlocked database with the Terminal Monitor:

        sql <database_name>

     2. SQL to lock the database:

        DISABLE PASSPHRASE '<user supplied passphrase>'; g

The SQL statement locks the database. New connect attempts to the database are rejected with a corresponding error. Sessions that connected previously can still access the data until they disconnect.

To make the database lock also immediately effective for already connected sessions, additionally issue the following SQL statement:

1. 1. 1. CALL X100(TERMINATE); g

• Unlock the encrypted database:
  1. 1. Connect to the locked database with the Terminal Monitor and option “-no_x100”:

        sql -no_x100 <database_name>

     2. SQL to unlock the database:

        ENABLE PASSPHRASE '<user supplied passphrase>'; g

The connection with the “-no_x100” option connects without access to the warehouse data, but allows the administrative SQL statement to unlock the database.

• Change the passphrase for the encrypted database:
  1. 1. Connect to the unlocked database with the Terminal Monitor:

        sql <database_name>

     2. SQL to change the passphrase:

        ALTER PASSPHRASE '<old user supplied passphrase>' TO
        '<new passphrase>'; g

Again, it is important that the administrator remembers the new passphrase.

After changing the passphrase for an encrypted database, it is recommended to perform a new database backup (a.k.a. “database checkpoint”) to ensure continued full database recoverability.

• When the database is no longer needed, destroy it:

  1. 1. destroydb <database_name>

Note that the passphrase of the encrypted database is not needed to destroy it. The command can only be performed by users with the proper privileges, i.e. the database owner and administrators.

This first blog post in the database security series explained the concept of encryption at rest and how transparent encryption — in Actian Vector called Database Encryption — is used.

The next blog post in this series will take a look at function-based encryption in Actian Vector.

The post Securing Your Data With Actian Vector appeared first on Actian.

Welcome to the first installment of my four-part blog series on HCL Informix® application modernization.

Organizations like yours face increasing pressure to modernize their legacy applications to remain competitive and meet customer needs. HCL Informix, a robust and reliable database platform, has been a cornerstone of many businesses for decades. Now, as technology advances and business needs change, HCL Informix can play a new role—helping you to reevaluate and modernize your applications.

In the HCL Informix Modernization Checklist, I outline four steps to planning your modernization journey:

1. Start building your business strategy
2. Evaluate your existing Informix database environment
3. Kick off your modernization project
4. Learn, optimize, and innovate

Throughout this modernization series, we will dedicate a blog to each of these steps, delving into the strategic considerations, technical approaches, and best practices so you can get your project started on the right track.

Start building your business strategy

Establish your application modernization objectives

The initial step in any application migration and modernization project is to clearly define the business problems you are trying to solve and optimize your project planning to best serve those needs. For example, you may be facing challenges with: 

• Security and compliance
• Stability and reliability 
• Performance bottlenecks and scalability 
• Web and modern APIs
• Technological obsolescence
• Cost inefficiencies

By defining these parameters, you can set a clear objective for your migration and modernization efforts. This will guide your decision-making process and help in selecting the right strategies and technologies for a successful transformation.

Envision the end result

Understanding the problem you want to address is crucial, but it’s equally important to develop a solution. Start by envisioning an ideal scenario. For instance, consider goals like:

• Real-time responses
• Scale to meet user demand
• Update applications with zero downtime
• Zero security incidents
• 100% connectivity with other applications
• Deliver the project on time and on budget
• Complete business continuity

Track progress with key performance indicators

Set key performance indicators (KPIs) to track progress toward your goals and objectives. This keeps leadership informed and motivates the team. Some sample KPIs might look like: 

Identify the capabilities you want to incorporate into your applications

With your vision in place, identify capabilities you wish to incorporate into your applications to help you meet your KPIs. Consider incorporating capabilities like:

• Cloud computing
• Third-party solutions and microservices
• Orchestration and automation
• DevOps practices
• APIs for better integration

Evaluate each capability and sketch an architecture diagram to determine if existing tools meet your needs. If not, identify new services required for your modernization project.

Get Your Modernization Checklist

For more best-practice approaches to modernizing your Informix applications, download the HCL Informix Modernization Checklist and stay tuned for the next blog in the series.

Get the Checklist >

Informix® is a trademark of IBM Corporation in at least one jurisdiction and is used under license.

The post The Essential Guide to Modernizing HCL Informix Applications (Part 1) appeared first on Actian.

Technology is changing every industry, and agriculture is no exception. The Internet of Things (IoT) and edge computing provide powerful tools to make traditional farming practices more efficient, sustainable, and data-driven. One affordable and versatile platform that can form the basis for such a smart agriculture system is the Raspberry Pi.

In this blog post, we will build a smart agriculture system using IoT devices to monitor soil moisture, temperature, and humidity levels across a farm. The goal is to optimize irrigation and ensure optimal growing conditions for crops. We’ll use a Raspberry Pi running Raspbian OS, Actian Zen Edge for database management, Zen Enterprise to handle the detected anomalies on the remote server database, and Python with the Zen ODBC interface for data handling. Additionally, we’ll leverage AWS SNS (Simple Notification Service) to send alerts for detected anomalies in real-time for immediate action.

Prerequisites

Before we start, ensure you have the following:

• A Raspberry Pi running Raspbian OS.
• Python installed on your Raspberry Pi.
• Actian Zen Edge database installed.
• PyODBC library installed.
• AWS SNS set up with an appropriate topic and access credentials.

Step 1: Setting Up the Raspberry Pi

First, update your Raspberry Pi and install the necessary libraries:

sudo apt-get update
sudo apt-get upgrade
sudo apt-get install python3-pip
pip3 install pyodbc boto3

Step 2: Install Actian Zen Edge

Follow the instructions on the Actian Zen Edge download page to download and install Actian Zen Edge on your Raspberry Pi.

Step 3: Create Tables in the Database

We need to create tables to store sensor data and anomalies. Connect to your Actian Zen Edge database and create the following table:

CREATE TABLE sensor_data (
    id identity PRIMARY KEY,
    timestamp DATETIME,
    soil_moisture FLOAT,
    temperature FLOAT,
    humidity FLOAT
);

Install Zen Enterprise, connect to the central database, and create the following table:

 CREATE TABLE anomalies (
    id identity PRIMARY KEY ,
    timestamp DATETIME,
    soil_moisture FLOAT,
    temperature FLOAT,
    humidity FLOAT,
    description longvarchar
);

Step 4: Define the Python Script

Now, let’s write the Python script to handle sensor data insertion, anomaly detection, and alerting via AWS SNS.

Anomaly Detection Logic

Define a function to check for anomalies based on predefined thresholds:

def check_for_anomalies(data):
    threshold = {'soil_moisture': 30.0, 'temperature': 35.0, 'humidity': 70.0}
    anomalies = []
    if data['soil_moisture'] < threshold['soil_moisture']:
        anomalies.append('Low soil moisture detected')
    if data['temperature'] > threshold['temperature']:
        anomalies.append('High temperature detected')
    if data['humidity'] > threshold['humidity']:
        anomalies.append('High humidity detected')
    return anomalies

Insert Sensor Data

Define a function to insert sensor data into the database:

import pyodbc

def insert_sensor_data(data):
    conn = pyodbc.connect('Driver={Pervasive ODBC 
Interface};servername=localhost;Port=1583;serverdsn=demodata;')
    cursor = conn.cursor()
    cursor.execute("INSERT INTO sensor_data (timestamp, soil_moisture, temperature, humidity) VALUES (?, ?, ?, ?)",
                   (data['timestamp'], data['soil_moisture'], data['temperature'], data['humidity']))
    conn.commit()
    cursor.close()
    conn.close()

Send Anomalies to the Remote Database

Define a function to send detected anomalies to the database:

def send_anomalies_to_server(anomaly_data):
    conn = pyodbc.connect('Driver={Pervasive ODBC Interface};servername=<remote server>;Port=1583;serverdsn=demodata;')
    cursor = conn.cursor()
    cursor.execute("INSERT INTO anomalies (timestamp, soil_moisture, temperature, humidity, description) VALUES (?, ?, ?, ?, ?)",
                   (anomaly_data['timestamp'], anomaly_data['soil_moisture'], anomaly_data['temperature'], anomaly_data['humidity'], anomaly_data['description']))
    conn.commit()
    cursor.close()
    conn.close()

Send Alerts Using AWS SNS

Define a function to send alerts using AWS SNS:

def send_alert(message):
    sns_client = boto3.client('sns', aws_access_key_id='Your key ID',
    aws_secret_access_key ='Your Access key’, region_name='your-region')
    topic_arn = 'arn:aws:sns:your-region:your-account-id:your-topic-name'
    response = sns_client.publish(
        TopicArn=topic_arn,
        Message=message,
        Subject='Anomaly Alert'
    )
    return response

Replace your-region, your-account-id, and your-topic-name with your actual AWS SNS topic details.

Step 5: Generate Sensor Data

Define a function to simulate real-world sensor data:

import random
import datetime

def generate_sensor_data():
    return {
        'timestamp': datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
        'soil_moisture': random.uniform(20.0, 40.0),
        'temperature': random.uniform(15.0, 45.0),
        'humidity': random.uniform(30.0, 80.0)
    }

Step 6: Main Function to Simulate Data Collection and Processing

Finally, put everything together in a main function:

def main():
    for _ in range(100):
        sensor_data = generate_sensor_data()
        insert_sensor_data(sensor_data)
        anomalies = check_for_anomalies(sensor_data)
        if anomalies:
            anomaly_data = {
                'timestamp': sensor_data['timestamp'],
                'soil_moisture': sensor_data['soil_moisture'],
                'temperature': sensor_data['temperature'],
                'humidity': sensor_data['humidity'],
                'description': ', '.join(anomalies)
            }
            send_anomalies_to_server(anomaly_data)
            send_alert(anomaly_data['description'])
if __name__ == "__main__":
    main()

Conclusion

And there you have it! By following these steps, you’ve successfully set up a basic smart agriculture system on a Raspberry Pi using Actian Zen Edge and Python. This system, which monitors soil moisture, temperature, and humidity levels, detects anomalies, stores data in databases, and sends notifications via AWS SNS, is a scalable solution for optimizing irrigation and ensuring optimal growing conditions for crops. Now, it’s your turn to apply this knowledge and contribute to the future of smart agriculture.

Remember to replace placeholders with your actual AWS SNS topic details and database connection details. Happy farming!

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